Science.gov

Sample records for adaptive system identification

  1. Multiclient Identification System Using Adaptive Probabilistic Model

    NASA Astrophysics Data System (ADS)

    Lin, Chin-Teng; Siana, Linda; Shou, Yu-Wen; Yang, Chien-Ting

    2010-12-01

    This paper aims at integrating detection and identification of human faces in a more practical and real-time face recognition system. The proposed face detection system is based on the cascade Adaboost method to improve the precision and robustness toward unstable surrounding lightings. Our Adaboost method innovates to adjust the environmental lighting conditions by histogram lighting normalization and to accurately locate the face regions by a region-based-clustering process as well. We also address on the problem of multi-scale faces in this paper by using 12 different scales of searching windows and 5 different orientations for each client in pursuit of the multi-view independent face identification. There are majorly two methodological parts in our face identification system, including PCA (principal component analysis) facial feature extraction and adaptive probabilistic model (APM). The structure of our implemented APM with a weighted combination of simple probabilistic functions constructs the likelihood functions by the probabilistic constraint in the similarity measures. In addition, our proposed method can online add a new client and update the information of registered clients due to the constructed APM. The experimental results eventually show the superior performance of our proposed system for both offline and real-time online testing.

  2. Identification of Infinite Dimensional Systems via Adaptive Wavelet Neural Networks

    DTIC Science & Technology

    1993-01-01

    We consider identification of distributed systems via adaptive wavelet neural networks (AWNNs). We take advantage of the multiresolution property of...wavelet systems and the computational structure of neural networks to approximate the unknown plant successively. A systematic approach is developed

  3. The reduced order model problem in distributed parameter systems adaptive identification and control. [adaptive control of flexible spacecraft

    NASA Technical Reports Server (NTRS)

    Johnson, C. R., Jr.; Lawrence, D. A.

    1981-01-01

    The reduced order model problem in distributed parameter systems adaptive identification and control is investigated. A comprehensive examination of real-time centralized adaptive control options for flexible spacecraft is provided.

  4. System identification, adaptive control and formation driving of farm tractors

    NASA Astrophysics Data System (ADS)

    Rekow, Andrew Karl Wilhelm

    Great increases in agricultural productivity and profitability can be gained by increasing the navigational control accuracy of a farm tractor. To maximize accuracy in the presence of environmental uncertainties, a novel technique for on-line parameter identification has been developed. This method combines the Extended Kalman Filter (EKF) and the Least Mean Square (LMS) algorithms and is used to identify key parameters which describe the dynamics of a farm tractor. This algorithm provides a 15:1 improvement in computational efficiency over the traditional EKF, while offering comparable convergence rates and noise rejection properties. Experimental data on a full-sized John Deere tractor shows a 25 percent improvement in lateral accuracy when using then adaptive controller versus a fixed controller over identical trajectories. In addition to parameter identification, farmers require formation driving capability for routine operations. Multiple farm vehicles work cooperatively together to accomplish a common goal. Several formation driving algorithms were developed for these varying requirements. An experimental implementation of a fully autonomous farm vehicle following a human operated lead vehicle demonstrated an accuracy of 10 centimeters in the in-track direction and 10 centimeters in the cross track direction.

  5. Multivariable adaptive identification and control for artificial pancreas systems.

    PubMed

    Turksoy, Kamuran; Quinn, Laurie; Littlejohn, Elizabeth; Cinar, Ali

    2014-03-01

    A constrained weighted recursive least squares method is proposed to provide recursive models with guaranteed stability and better performance than models based on regular identification methods in predicting the variations of blood glucose concentration in patients with Type 1 Diabetes. Use of physiological information from a sports armband improves glucose concentration prediction and enables earlier recognition of the effects of physical activity on glucose concentration. Generalized predictive controllers (GPC) based on these recursive models are developed. The performance of GPC for artificial pancreas systems is illustrated by simulations with UVa-Padova simulator and clinical studies. The controllers developed are good candidates for artificial pancreas systems with no announcements from patients.

  6. Adaptive identification and control of structural dynamics systems using recursive lattice filters

    NASA Technical Reports Server (NTRS)

    Sundararajan, N.; Montgomery, R. C.; Williams, J. P.

    1985-01-01

    A new approach for adaptive identification and control of structural dynamic systems by using least squares lattice filters thar are widely used in the signal processing area is presented. Testing procedures for interfacing the lattice filter identification methods and modal control method for stable closed loop adaptive control are presented. The methods are illustrated for a free-free beam and for a complex flexible grid, with the basic control objective being vibration suppression. The approach is validated by using both simulations and experimental facilities available at the Langley Research Center.

  7. Development of an adaptive failure detection and identification system for detecting aircraft control element failures

    NASA Technical Reports Server (NTRS)

    Bundick, W. Thomas

    1990-01-01

    A methodology for designing a failure detection and identification (FDI) system to detect and isolate control element failures in aircraft control systems is reviewed. An FDI system design for a modified B-737 aircraft resulting from this methodology is also reviewed, and the results of evaluating this system via simulation are presented. The FDI system performed well in a no-turbulence environment, but it experienced an unacceptable number of false alarms in atmospheric turbulence. An adaptive FDI system, which adjusts thresholds and other system parameters based on the estimated turbulence level, was developed and evaluated. The adaptive system performed well over all turbulence levels simulated, reliably detecting all but the smallest magnitude partially-missing-surface failures.

  8. Performance study of LMS based adaptive algorithms for unknown system identification

    NASA Astrophysics Data System (ADS)

    Javed, Shazia; Ahmad, Noor Atinah

    2014-07-01

    Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.

  9. Performance study of LMS based adaptive algorithms for unknown system identification

    SciTech Connect

    Javed, Shazia; Ahmad, Noor Atinah

    2014-07-10

    Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.

  10. Adaptive System Identification for Estimating Future Glucose Concentrations and Hypoglycemia Alarms.

    PubMed

    Eren-Oruklu, Meriyan; Cinar, Ali; Rollins, Derrick K; Quinn, Lauretta

    2012-08-01

    Many patients with diabetes experience high variability in glucose concentrations that includes prolonged hyperglycemia or hypoglycemia. Models predicting a subject's future glucose concentrations can be used for preventing such conditions by providing early alarms. This paper presents a time-series model that captures dynamical changes in the glucose metabolism. Adaptive system identification is proposed to estimate model parameters which enable the adaptation of the model to inter-/intra-subject variation and glycemic disturbances. It consists of online parameter identification using the weighted recursive least squares method and a change detection strategy that monitors variation in model parameters. Univariate models developed from a subject's continuous glucose measurements are compared to multivariate models that are enhanced with continuous metabolic, physical activity and lifestyle information from a multi-sensor body monitor. A real life application for the proposed algorithm is demonstrated on early (30 min in advance) hypoglycemia detection.

  11. Adaptive modeling, identification, and control of dynamic structural systems. I. Theory

    USGS Publications Warehouse

    Safak, Erdal

    1989-01-01

    A concise review of the theory of adaptive modeling, identification, and control of dynamic structural systems based on discrete-time recordings is presented. Adaptive methods have four major advantages over the classical methods: (1) Removal of the noise from the signal is done over the whole frequency band; (2) time-varying characteristics of systems can be tracked; (3) systems with unknown characteristics can be controlled; and (4) a small segment of the data is needed during the computations. Included in the paper are the discrete-time representation of single-input single-output (SISO) systems, models for SISO systems with noise, the concept of stochastic approximation, recursive prediction error method (RPEM) for system identification, and the adaptive control. Guidelines for model selection and model validation and the computational aspects of the method are also discussed in the paper. The present paper is the first of two companion papers. The theory given in the paper is limited to that which is necessary to follow the examples for applications in structural dynamics presented in the second paper.

  12. Parametric recursive system identification and self-adaptive modeling of the human energy metabolism for adaptive control of fat weight.

    PubMed

    Őri, Zsolt P

    2016-08-03

    A mathematical model has been developed to facilitate indirect measurements of difficult to measure variables of the human energy metabolism on a daily basis. The model performs recursive system identification of the parameters of the metabolic model of the human energy metabolism using the law of conservation of energy and principle of indirect calorimetry. Self-adaptive models of the utilized energy intake prediction, macronutrient oxidation rates, and daily body composition changes were created utilizing Kalman filter and the nominal trajectory methods. The accuracy of the models was tested in a simulation study utilizing data from the Minnesota starvation and overfeeding study. With biweekly macronutrient intake measurements, the average prediction error of the utilized carbohydrate intake was -23.2 ± 53.8 kcal/day, fat intake was 11.0 ± 72.3 kcal/day, and protein was 3.7 ± 16.3 kcal/day. The fat and fat-free mass changes were estimated with an error of 0.44 ± 1.16 g/day for fat and -2.6 ± 64.98 g/day for fat-free mass. The daily metabolized macronutrient energy intake and/or daily macronutrient oxidation rate and the daily body composition change from directly measured serial data are optimally predicted with a self-adaptive model with Kalman filter that uses recursive system identification.

  13. Lithofacies identification using multiple adaptive resonance theory neural networks and group decision expert system

    USGS Publications Warehouse

    Chang, H.-C.; Kopaska-Merkel, D. C.; Chen, H.-C.; Rocky, Durrans S.

    2000-01-01

    Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies identification from core data are costly and different geologists may provide different interpretations. In this paper, we present a low-cost intelligent system consisting of three adaptive resonance theory neural networks and a rule-based expert system to consistently and objectively identify lithofacies from well-log data. The input data are altered into different forms representing different perspectives of observation of lithofacies. Each form of input is processed by a different adaptive resonance theory neural network. Among these three adaptive resonance theory neural networks, one neural network processes the raw continuous data, another processes categorial data, and the third processes fuzzy-set data. Outputs from these three networks are then combined by the expert system using fuzzy inference to determine to which facies the input data should be assigned. Rules are prioritized to emphasize the importance of firing order. This new approach combines the learning ability of neural networks, the adaptability of fuzzy logic, and the expertise of geologists to infer facies of the rocks. This approach is applied to the Appleton Field, an oil field located in Escambia County, Alabama. The hybrid intelligence system predicts lithofacies identity from log data with 87.6% accuracy. This prediction is more accurate than those of single adaptive resonance theory networks, 79.3%, 68.0% and 66.0%, using raw, fuzzy-set, and categorical data, respectively, and by an error-backpropagation neural network, 57.3%. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.

  14. Systems identification and the adaptive management of waterfowl in the United States

    USGS Publications Warehouse

    Williams, B.K.; Nichols, J.D.

    2001-01-01

    Waterfowl management in the United States is one of the more visible conservation success stories in the United States. It is authorized and supported by appropriate legislative authorities, based on large-scale monitoring programs, and widely accepted by the public. The process is one of only a limited number of large-scale examples of effective collaboration between research and management, integrating scientific information with management in a coherent framework for regulatory decision-making. However, harvest management continues to face some serious technical problems, many of which focus on sequential identification of the resource system in a context of optimal decision-making. The objective of this paper is to provide a theoretical foundation of adaptive harvest management, the approach currently in use in the United States for regulatory decision-making. We lay out the legal and institutional framework for adaptive harvest management and provide a formal description of regulatory decision-making in terms of adaptive optimization. We discuss some technical and institutional challenges in applying adaptive harvest management and focus specifically on methods of estimating resource states for linear resource systems.

  15. An adaptive wavelet neural network for spatio-temporal system identification.

    PubMed

    Wei, H L; Billings, S A; Zhao, Y F; Guo, L Z

    2010-12-01

    Starting from the basic concept of coupled map lattices, a new family of adaptive wavelet neural networks (AWNN) is introduced for spatio-temporal system identification, by combining an efficient wavelet representation with a coupled map lattice model. A new orthogonal projection pursuit (OPP) method, coupled with a particle swarm optimization (PSO) algorithm, is proposed for augmenting the proposed network. A novel two-stage hybrid training scheme is developed for constructing a parsimonious network model. In the first stage, by applying the orthogonal projection pursuit algorithm, significant wavelet neurons are adaptively and successively recruited into the network, where adjustable parameters of the associated wavelet neurons are optimized using a particle swarm optimizer. The resultant network model, obtained in the first stage, may however be redundant. In the second stage, an orthogonal least squares algorithm is then applied to refine and improve the initially trained network by removing redundant wavelet neurons from the network. The proposed two-stage hybrid training procedure can generally produce a parsimonious network model, where a ranked list of wavelet neurons, according to the capability of each neuron to represent the total variance in the system output signal is produced. Two spatio-temporal system identification examples are presented to demonstrate the performance of the proposed new modelling framework.

  16. Identification and adaptive neural network control of a DC motor system with dead-zone characteristics.

    PubMed

    Peng, Jinzhu; Dubay, Rickey

    2011-10-01

    In this paper, an adaptive control approach based on the neural networks is presented to control a DC motor system with dead-zone characteristics (DZC), where two neural networks are proposed to formulate the traditional identification and control approaches. First, a Wiener-type neural network (WNN) is proposed to identify the motor DZC, which formulates the Wiener model with a linear dynamic block in cascade with a nonlinear static gain. Second, a feedforward neural network is proposed to formulate the traditional PID controller, termed as PID-type neural network (PIDNN), which is then used to control and compensate for the DZC. In this way, the DC motor system with DZC is identified by the WNN identifier, which provides model information to the PIDNN controller in order to make it adaptive. Back-propagation algorithms are used to train both neural networks. Also, stability and convergence analysis are conducted using the Lyapunov theorem. Finally, experiments on the DC motor system demonstrated accurate identification and good compensation for dead-zone with improved control performance over the conventional PID control.

  17. An on-line equivalent system identification scheme for adaptive control. Ph.D. Thesis - Stanford Univ.

    NASA Technical Reports Server (NTRS)

    Sliwa, S. M.

    1984-01-01

    A prime obstacle to the widespread use of adaptive control is the degradation of performance and possible instability resulting from the presence of unmodeled dynamics. The approach taken is to explicitly include the unstructured model uncertainty in the output error identification algorithm. The order of the compensator is successively increased by including identified modes. During this model building stage, heuristic rules are used to test for convergence prior to designing compensators. Additionally, the recursive identification algorithm as extended to multi-input, multi-output systems. Enhancements were also made to reduce the computational burden of an algorithm for obtaining minimal state space realizations from the inexact, multivariate transfer functions which result from the identification process. A number of potential adaptive control applications for this approach are illustrated using computer simulations. Results indicated that when speed of adaptation and plant stability are not critical, the proposed schemes converge to enhance system performance.

  18. Aircraft Abnormal Conditions Detection, Identification, and Evaluation Using Innate and Adaptive Immune Systems Interaction

    NASA Astrophysics Data System (ADS)

    Al Azzawi, Dia

    Abnormal flight conditions play a major role in aircraft accidents frequently causing loss of control. To ensure aircraft operation safety in all situations, intelligent system monitoring and adaptation must rely on accurately detecting the presence of abnormal conditions as soon as they take place, identifying their root cause(s), estimating their nature and severity, and predicting their impact on the flight envelope. Due to the complexity and multidimensionality of the aircraft system under abnormal conditions, these requirements are extremely difficult to satisfy using existing analytical and/or statistical approaches. Moreover, current methodologies have addressed only isolated classes of abnormal conditions and a reduced number of aircraft dynamic parameters within a limited region of the flight envelope. This research effort aims at developing an integrated and comprehensive framework for the aircraft abnormal conditions detection, identification, and evaluation based on the artificial immune systems paradigm, which has the capability to address the complexity and multidimensionality issues related to aircraft systems. Within the proposed framework, a novel algorithm was developed for the abnormal conditions detection problem and extended to the abnormal conditions identification and evaluation. The algorithm and its extensions were inspired from the functionality of the biological dendritic cells (an important part of the innate immune system) and their interaction with the different components of the adaptive immune system. Immunity-based methodologies for re-assessing the flight envelope at post-failure and predicting the impact of the abnormal conditions on the performance and handling qualities are also proposed and investigated in this study. The generality of the approach makes it applicable to any system. Data for artificial immune system development were collected from flight tests of a supersonic research aircraft within a motion-based flight

  19. Design of adaptive reconfigurable control systems using extended-Kalman-filter-based system identification and eigenstructure assignments

    NASA Astrophysics Data System (ADS)

    Wang, Xudong; Syrmos, Vassilis L.

    2004-07-01

    In this paper, an adaptive reconfigurable control system based on extended Kalman filter approach and eigenstructure assignments is proposed. System identification is carried out using an extended Kalman filter (EKF) approach. An eigenstructure assignment (EA) technique is applied for reconfigurable feedback control law design to recover the system dynamic performance. The reconfigurable feedforward controllers are designed to achieve the steady-state tracking using input weighting approach. The proposed scheme can identify not only actuator and sensor variations, but also changes in the system structures using the extended Kalman filtering method. The overall design is robust with respect to uncertainties in the state-space matrices of the reconfigured system. To illustrate the effectiveness of the proposed reconfigurable control system design technique, an aircraft longitudinal vertical takeoff and landing (VTOL) control system is used to demonstrate the reconfiguration procedure.

  20. The reduced order model problem in distributed parameter systems adaptive identification and control

    NASA Technical Reports Server (NTRS)

    Johnson, C. R., Jr.

    1980-01-01

    The research concerning the reduced order model problem in distributed parameter systems is reported. The adaptive control strategy was chosen for investigation in the annular momentum control device. It is noted, that if there is no observation spill over, and no model errors, an indirect adaptive control strategy can be globally stable. Recent publications concerning adaptive control are included.

  1. Structure identification of an uncertain network coupled with complex-variable chaotic systems via adaptive impulsive control

    NASA Astrophysics Data System (ADS)

    Liu, Dan-Feng; Wu, Zhao-Yan; Ye, Qing-Ling

    2014-04-01

    In this paper, structure identification of an uncertain network coupled with complex-variable chaotic systems is investigated. Both the topological structure and the system parameters can be unknown and need to be identified. Based on impulsive stability theory and the Lyapunov function method, an impulsive control scheme combined with an adaptive strategy is adopted to design effective and universal network estimators. The restriction on the impulsive interval is relaxed by adopting an adaptive strategy. Further, the proposed method can monitor the online switching topology effectively. Several numerical simulations are provided to illustrate the effectiveness of the theoretical results.

  2. Minimum variance system identification with application to digital adaptive flight control

    NASA Technical Reports Server (NTRS)

    Kotob, S.; Kaufman, H.

    1975-01-01

    A new on-line minimum variance filter for the identification of systems with additive and multiplicative noise is described which embodies both accuracy and computational efficiency. The resulting filter is shown to use both the covariance of the parameter vector itself and the covariance of the error in identification. A bias reduction scheme can be used to yield asymptotically unbiased estimates. Experimental results for simulated linearized lateral aircraft motion in a digital closed loop mode are presented, showing the utility of the identification schemes.

  3. A system identification analysis of neural adaptation dynamics and nonlinear responses in the local reflex control of locust hind limbs.

    PubMed

    Dewhirst, Oliver P; Angarita-Jaimes, Natalia; Simpson, David M; Allen, Robert; Newland, Philip L

    2013-02-01

    Nonlinear type system identification models coupled with white noise stimulation provide an experimentally convenient and quick way to investigate the often complex and nonlinear interactions between the mechanical and neural elements of reflex limb control systems. Previous steady state analysis has allowed the neurons in such systems to be categorised by their sensitivity to position, velocity or acceleration (dynamics) and has improved our understanding of network function. These neurons, however, are known to adapt their output amplitude or spike firing rate during repetitive stimulation and this transient response may be more important than the steady state response for reflex control. In the current study previously used system identification methods are developed and applied to investigate both steady state and transient dynamic and nonlinear changes in the neural circuit responsible for controlling reflex movements of the locust hind limbs. Through the use of a parsimonious model structure and Monte Carlo simulations we conclude that key system dynamics remain relatively unchanged during repetitive stimulation while output amplitude adaptation is occurring. Whilst some evidence of a significant change was found in parts of the systems nonlinear response, the effect was small and probably of little physiological relevance. Analysis using biologically more realistic stimulation reinforces this conclusion.

  4. A knowledge-based approach to identification and adaptation in dynamical systems control

    NASA Technical Reports Server (NTRS)

    Glass, B. J.; Wong, C. M.

    1988-01-01

    Artificial intelligence techniques are applied to the problems of model form and parameter identification of large-scale dynamic systems. The object-oriented knowledge representation is discussed in the context of causal modeling and qualitative reasoning. Structured sets of rules are used for implementing qualitative component simulations, for catching qualitative discrepancies and quantitative bound violations, and for making reconfiguration and control decisions that affect the physical system. These decisions are executed by backward-chaining through a knowledge base of control action tasks. This approach was implemented for two examples: a triple quadrupole mass spectrometer and a two-phase thermal testbed. Results of tests with both of these systems demonstrate that the software replicates some or most of the functionality of a human operator, thereby reducing the need for a human-in-the-loop in the lower levels of control of these complex systems.

  5. Assessment of Multi-Joint Coordination and Adaptation in Standing Balance: A Novel Device and System Identification Technique.

    PubMed

    Engelhart, Denise; Schouten, Alfred C; Aarts, Ronald G K M; van der Kooij, Herman

    2015-11-01

    The ankles and hips play an important role in maintaining standing balance and the coordination between joints adapts with task and conditions, like the disturbance magnitude and type, and changes with age. Assessment of multi-joint coordination requires the application of multiple continuous and independent disturbances and closed loop system identification techniques (CLSIT). This paper presents a novel device, the double inverted pendulum perturbator (DIPP), which can apply disturbing forces at the hip level and between the shoulder blades. In addition to the disturbances, the device can provide force fields to study adaptation of multi-joint coordination. The performance of the DIPP and a novel CLSIT was assessed by identifying a system with known mechanical properties and model simulations. A double inverted pendulum was successfully identified, while force fields were able to keep the pendulum upright. The estimated dynamics were similar as the theoretical derived dynamics. The DIPP has a sufficient bandwidth of 7 Hz to identify multi-joint coordination dynamics. An experiment with human subjects where a stabilizing force field was rendered at the hip (1500 N/m), showed that subjects adapt by lowering their control actions around the ankles. The stiffness from upper and lower segment motion to ankle torque dropped with 30% and 48%, respectively. Our methods allow to study (pathological) changes in multi-joint coordination as well as adaptive capacity to maintain standing balance.

  6. Comparative system identification of flower tracking performance in three hawkmoth species reveals adaptations for dim light vision.

    PubMed

    Stöckl, Anna L; Kihlström, Klara; Chandler, Steven; Sponberg, Simon

    2017-04-05

    Flight control in insects is heavily dependent on vision. Thus, in dim light, the decreased reliability of visual signal detection also prompts consequences for insect flight. We have an emerging understanding of the neural mechanisms that different species employ to adapt the visual system to low light. However, much less explored are comparative analyses of how low light affects the flight behaviour of insect species, and the corresponding links between physiological adaptations and behaviour. We investigated whether the flower tracking behaviour of three hawkmoth species with different diel activity patterns revealed luminance-dependent adaptations, using a system identification approach. We found clear luminance-dependent differences in flower tracking in all three species, which were explained by a simple luminance-dependent delay model, which generalized across species. We discuss physiological and anatomical explanations for the variance in tracking responses, which could not be explained by such simple models. Differences between species could not be explained by the simple delay model. However, in several cases, they could be explained through the addition on a second model parameter, a simple scaling term, that captures the responsiveness of each species to flower movements. Thus, we demonstrate here that much of the variance in the luminance-dependent flower tracking responses of hawkmoths with different diel activity patterns can be captured by simple models of neural processing.This article is part of the themed issue 'Vision in dim light'.

  7. Adaptation of adaptive optics systems.

    NASA Astrophysics Data System (ADS)

    Xin, Yu; Zhao, Dazun; Li, Chen

    1997-10-01

    In the paper, a concept of an adaptation of adaptive optical system (AAOS) is proposed. The AAOS has certain real time optimization ability against the variation of the brightness of detected objects m, atmospheric coherence length rO and atmospheric time constant τ by means of changing subaperture number and diameter, dynamic range, and system's temporal response. The necessity of AAOS using a Hartmann-Shack wavefront sensor and some technical approaches are discussed. Scheme and simulation of an AAOS with variable subaperture ability by use of both hardware and software are presented as an example of the system.

  8. The reduced order model problem in distributed parameter systems adaptive identification and control. [large space structures

    NASA Technical Reports Server (NTRS)

    Johnson, C. R., Jr.; Lawrence, D.

    1981-01-01

    The basic assumption that a large space structure can be decoupled preceding the application of reduced order active control was considered and alternative solutions to the control of such structures (in contrast to the strict modal control) were investigated. The transfer function matrix from the actuators to the sensors was deemed to be a reasonable candidate. More refined models from multivariable systems theory were studied and recent results in the multivariable control field were compared with respect to theoretical deficiencies and likely problems in application to large space structures.

  9. Dynamic modeling of breast tissue with application of model reference adaptive system identification technique based on clinical robot-assisted palpation.

    PubMed

    Keshavarz, M; Mojra, A

    2015-11-01

    Accurate identification of breast tissue's dynamic behavior in physical examination is critical to successful diagnosis and treatment. In this study a model reference adaptive system identification (MRAS) algorithm is utilized to estimate the dynamic behavior of breast tissue from mechanical stress-strain datasets. A robot-assisted device (Robo-Tac-BMI) is going to mimic physical palpation on a 45 year old woman having a benign mass in the left breast. Stress-strain datasets will be collected over 14 regions of both breasts in a specific period of time. Then, a 2nd order linear model is adapted to the experimental datasets. It was confirmed that a unique dynamic model with maximum error about 0.89% is descriptive of the breast tissue behavior meanwhile mass detection may be achieved by 56.1% difference from the normal tissue.

  10. A novel online adaptive time delay identification technique

    NASA Astrophysics Data System (ADS)

    Bayrak, Alper; Tatlicioglu, Enver

    2016-05-01

    Time delay is a phenomenon which is common in signal processing, communication, control applications, etc. The special feature of time delay that makes it attractive is that it is a commonly faced problem in many systems. A literature search on time-delay identification highlights the fact that most studies focused on numerical solutions. In this study, a novel online adaptive time-delay identification technique is proposed. This technique is based on an adaptive update law through a minimum-maximum strategy which is firstly applied to time-delay identification. In the design of the adaptive identification law, Lyapunov-based stability analysis techniques are utilised. Several numerical simulations were conducted with Matlab/Simulink to evaluate the performance of the proposed technique. It is numerically demonstrated that the proposed technique works efficiently in identifying both constant and disturbed time delays, and is also robust to measurement noise.

  11. CONTROL SYSTEM IDENTIFICATION THROUGH MODEL MODULATION METHODS

    DTIC Science & Technology

    identification has been achieved by using model modulation techniques to drive dynamic models into correspondence with operating control systems. The system ... identification then proceeded from examination of the model and the adaptive loop. The model modulation techniques applied to adaptive control

  12. Adaptive Modal Identification for Flutter Suppression Control

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Drew, Michael; Swei, Sean S.

    2016-01-01

    In this paper, we will develop an adaptive modal identification method for identifying the frequencies and damping of a flutter mode based on model-reference adaptive control (MRAC) and least-squares methods. The least-squares parameter estimation will achieve parameter convergence in the presence of persistent excitation whereas the MRAC parameter estimation does not guarantee parameter convergence. Two adaptive flutter suppression control approaches are developed: one based on MRAC and the other based on the least-squares method. The MRAC flutter suppression control is designed as an integral part of the parameter estimation where the feedback signal is used to estimate the modal information. On the other hand, the separation principle of control and estimation is applied to the least-squares method. The least-squares modal identification is used to perform parameter estimation.

  13. Adaptive infinite impulse response system identification using modified-interior search algorithm with Lèvy flight.

    PubMed

    Kumar, Manjeet; Rawat, Tarun Kumar; Aggarwal, Apoorva

    2017-03-01

    In this paper, a new meta-heuristic optimization technique, called interior search algorithm (ISA) with Lèvy flight is proposed and applied to determine the optimal parameters of an unknown infinite impulse response (IIR) system for the system identification problem. ISA is based on aesthetics, which is commonly used in interior design and decoration processes. In ISA, composition phase and mirror phase are applied for addressing the nonlinear and multimodal system identification problems. System identification using modified-ISA (M-ISA) based method involves faster convergence, single parameter tuning and does not require derivative information because it uses a stochastic random search using the concepts of Lèvy flight. A proper tuning of control parameter has been performed in order to achieve a balance between intensification and diversification phases. In order to evaluate the performance of the proposed method, mean square error (MSE), computation time and percentage improvement are considered as the performance measure. To validate the performance of M-ISA based method, simulations has been carried out for three benchmarked IIR systems using same order and reduced order system. Genetic algorithm (GA), particle swarm optimization (PSO), cat swarm optimization (CSO), cuckoo search algorithm (CSA), differential evolution using wavelet mutation (DEWM), firefly algorithm (FFA), craziness based particle swarm optimization (CRPSO), harmony search (HS) algorithm, opposition based harmony search (OHS) algorithm, hybrid particle swarm optimization-gravitational search algorithm (HPSO-GSA) and ISA are also used to model the same examples and simulation results are compared. Obtained results confirm the efficiency of the proposed method.

  14. Driver Adaptive Warning Systems

    DTIC Science & Technology

    1998-03-01

    this threshold, an alarm is triggered. Since TLC based systems can have user defined thresholds, a warning can be given as early as desired. However, the...Driver Adaptive Warning Systems Thesis Proposal Parag H. Batavia CMU-RI-TR-98-07 The Robotics Institute Carnegie Mellon University Pittsburgh...control number. 1. REPORT DATE MAR 1998 2. REPORT TYPE 3. DATES COVERED 00-00-1998 to 00-00-1998 4. TITLE AND SUBTITLE Driver Adaptive Warning

  15. Adaptive Identification and Control of Flow-Induced Cavity Oscillations

    NASA Technical Reports Server (NTRS)

    Kegerise, M. A.; Cattafesta, L. N.; Ha, C.

    2002-01-01

    Progress towards an adaptive self-tuning regulator (STR) for the cavity tone problem is discussed in this paper. Adaptive system identification algorithms were applied to an experimental cavity-flow tested as a prerequisite to control. In addition, a simple digital controller and a piezoelectric bimorph actuator were used to demonstrate multiple tone suppression. The control tests at Mach numbers of 0.275, 0.40, and 0.60 indicated approx. = 7dB tone reductions at multiple frequencies. Several different adaptive system identification algorithms were applied at a single freestream Mach number of 0.275. Adaptive finite-impulse response (FIR) filters of orders up to N = 100 were found to be unsuitable for modeling the cavity flow dynamics. Adaptive infinite-impulse response (IIR) filters of comparable order better captured the system dynamics. Two recursive algorithms, the least-mean square (LMS) and the recursive-least square (RLS), were utilized to update the adaptive filter coefficients. Given the sample-time requirements imposed by the cavity flow dynamics, the computational simplicity of the least mean squares (LMS) algorithm is advantageous for real-time control.

  16. Control Oriented System Identification

    DTIC Science & Technology

    1993-08-01

    The research goals for this grant were to obtain algorithms for control oriented system identification is to construct dynamical models of systems...and measured information. Algorithms for this type of nonlinear system identification have been given that produce models suitable for gain scheduled

  17. NEEDS - Information Adaptive System

    NASA Technical Reports Server (NTRS)

    Kelly, W. L.; Benz, H. F.; Meredith, B. D.

    1980-01-01

    The Information Adaptive System (IAS) is an element of the NASA End-to-End Data System (NEEDS) Phase II and is focused toward onboard image processing. The IAS is a data preprocessing system which is closely coupled to the sensor system. Some of the functions planned for the IAS include sensor response nonuniformity correction, geometric correction, data set selection, data formatting, packetization, and adaptive system control. The inclusion of these sensor data preprocessing functions onboard the spacecraft will significantly improve the extraction of information from the sensor data in a timely and cost effective manner, and provide the opportunity to design sensor systems which can be reconfigured in near real-time for optimum performance. The purpose of this paper is to present the preliminary design of the IAS and the plans for its development.

  18. In-Flight System Identification

    NASA Technical Reports Server (NTRS)

    Morelli, Eugene A.

    1998-01-01

    A method is proposed and studied whereby the system identification cycle consisting of experiment design and data analysis can be repeatedly implemented aboard a test aircraft in real time. This adaptive in-flight system identification scheme has many advantages, including increased flight test efficiency, adaptability to dynamic characteristics that are imperfectly known a priori, in-flight improvement of data quality through iterative input design, and immediate feedback of the quality of flight test results. The technique uses equation error in the frequency domain with a recursive Fourier transform for the real time data analysis, and simple design methods employing square wave input forms to design the test inputs in flight. Simulation examples are used to demonstrate that the technique produces increasingly accurate model parameter estimates resulting from sequentially designed and implemented flight test maneuvers. The method has reasonable computational requirements, and could be implemented aboard an aircraft in real time.

  19. Multiprocessor Adaptive Control Of A Dynamic System

    NASA Technical Reports Server (NTRS)

    Juang, Jer-Nan; Hyland, David C.

    1995-01-01

    Architecture for fully autonomous digital electronic control system developed for use in identification and adaptive control of dynamic system. Architecture modular and hierarchical. Combines relatively simple, standardized processing units into complex parallel-processing subsystems. Although architecture based on neural-network concept, processing units themselves not neural networks; processing units implemented by programming of currently available microprocessors.

  20. Author Identification Systems

    ERIC Educational Resources Information Center

    Wagner, A. Ben

    2009-01-01

    Many efforts are currently underway to disambiguate author names and assign unique identification numbers so that publications by a given scholar can be reliably grouped together. This paper reviews a number of operational and in-development services. Some systems like ResearcherId.Com depend on self-registration and self-identification of a…

  1. Adaptive CT scanning system

    SciTech Connect

    Sampayan, Stephen E.

    2016-11-22

    Apparatus, systems, and methods that provide an X-ray interrogation system having a plurality of stationary X-ray point sources arranged to substantially encircle an area or space to be interrogated. A plurality of stationary detectors are arranged to substantially encircle the area or space to be interrogated, A controller is adapted to control the stationary X-ray point sources to emit X-rays one at a time, and to control the stationary detectors to detect the X-rays emitted by the stationary X-ray point sources.

  2. Quantum system identification.

    PubMed

    Burgarth, Daniel; Yuasa, Kazuya

    2012-02-24

    The aim of quantum system identification is to estimate the ingredients inside a black box, in which some quantum-mechanical unitary process takes place, by just looking at its input-output behavior. Here we establish a basic and general framework for quantum system identification, that allows us to classify how much knowledge about the quantum system is attainable, in principle, from a given experimental setup. We show that controllable closed quantum systems can be estimated up to unitary conjugation. Prior knowledge on some elements of the black box helps the system identification. We present an example in which a Bell measurement is more efficient to identify the system. When the topology of the system is known, the framework enables us to establish a general criterion for the estimability of the coupling constants in its Hamiltonian.

  3. Adaptive Control of Nonlinear and Stochastic Systems

    DTIC Science & Technology

    1991-01-14

    Hernmndez-Lerma and S.I. Marcus, Nonparametric adaptive control of dis- crete time partially observable stochastic systems, Journal of Mathematical Analysis and Applications 137... Journal of Mathematical Analysis and Applications 137 (1989), 485-514. [19] A. Arapostathis and S.I. Marcus, Analysis of an identification algorithm

  4. Self-Tuning Adaptive-Controller Using Online Frequency Identification

    NASA Technical Reports Server (NTRS)

    Chiang, W. W.; Cannon, R. H., Jr.

    1985-01-01

    A real time adaptive controller was designed and tested successfully on a fourth order laboratory dynamic system which features very low structural damping and a noncolocated actuator sensor pair. The controller, implemented in a digital minicomputer, consists of a state estimator, a set of state feedback gains, and a frequency locked loop (FLL) for real time parameter identification. The FLL can detect the closed loop natural frequency of the system being controlled, calculate the mismatch between a plant parameter and its counterpart in the state estimator, and correct the estimator parameter in real time. The adaptation algorithm can correct the controller error and stabilize the system for more than 50% variation in the plant natural frequency, compared with a 10% stability margin in frequency variation for a fixed gain controller having the same performance at the nominal plant condition. After it has locked to the correct plant frequency, the adaptive controller works as well as the fixed gain controller does when there is no parameter mismatch. The very rapid convergence of this adaptive system is demonstrated experimentally, and can also be proven with simple root locus methods.

  5. Optimized System Identification

    NASA Technical Reports Server (NTRS)

    Juang, Jer-Nan; Longman, Richard W.

    1999-01-01

    In system identification, one usually cares most about finding a model whose outputs are as close as possible to the true system outputs when the same input is applied to both. However, most system identification algorithms do not minimize this output error. Often they minimize model equation error instead, as in typical least-squares fits using a finite-difference model, and it is seen here that this distinction is significant. Here, we develop a set of system identification algorithms that minimize output error for multi-input/multi-output and multi-input/single-output systems. This is done with sequential quadratic programming iterations on the nonlinear least-squares problems, with an eigendecomposition to handle indefinite second partials. This optimization minimizes a nonlinear function of many variables, and hence can converge to local minima. To handle this problem, we start the iterations from the OKID (Observer/Kalman Identification) algorithm result. Not only has OKID proved very effective in practice, it minimizes an output error of an observer which has the property that as the data set gets large, it converges to minimizing the criterion of interest here. Hence, it is a particularly good starting point for the nonlinear iterations here. Examples show that the methods developed here eliminate the bias that is often observed using any system identification methods of either over-estimating or under-estimating the damping of vibration modes in lightly damped structures.

  6. Optimal Inputs for System Identification.

    DTIC Science & Technology

    1995-09-01

    The derivation of the power spectral density of the optimal input for system identification is addressed in this research. Optimality is defined in...identification potential of general System Identification algorithms, a new and efficient System Identification algorithm that employs Iterated Weighted Least

  7. Common formalism for adaptive identification in signal processing and control

    NASA Astrophysics Data System (ADS)

    Macchi, O.

    1991-08-01

    The transversal and recursive approaches to adaptive identification are compared. ARMA modeling in signal processing, and identification in the indirect approach to control are developed in parallel. Adaptivity succeeds because the estimate is a linear function of the variable parameters for transversal identification. Control and signal processing can be imbedded in a unified well-established formalism that guarantees convergence of the adaptive parameters. For recursive identification, the estimate is a nonlinear function of the parameters, possibly resulting in nonuniqueness of the solution, in wandering and even instability of adaptive algorithms. The requirement for recursivity originates in the structure of the signal (MA-part) in signal processing. It is caused by the output measurement noise in control.

  8. An adaptive identification and control scheme for large space structures

    NASA Technical Reports Server (NTRS)

    Carroll, J. V.

    1988-01-01

    A unified identification and control scheme capable of achieving space at form performance objectives under nominal or failure conditions is described. Preliminary results are also presented, showing that the methodology offers much promise for effective robust control of large space structures. The control method is a multivariable, adaptive, output predictive controller called Model Predictive Control (MPC). MPC uses a state space model and input reference trajectories of set or tracking points to adaptively generate optimum commands. For a fixed model, MPC processes commands with great efficiency, and is also highly robust. A key feature of MPC is its ability to control either nonminimum phase or open loop unstable systems. As an output controller, MPC does not explicitly require full state feedback, as do most multivariable (e.g., Linear Quadratic) methods. Its features are very useful in LSS operations, as they allow non-collocated actuators and sensors. The identification scheme is based on canonical variate analysis (CVA) of input and output data. The CVA technique is particularly suited for the measurement and identification of structural dynamic processes - that is, unsteady transient or dynamically interacting processes such as between aerodynamics and structural deformation - from short, noisy data. CVA is structured so that the identification can be done in real or near real time, using computationally stable algorithms. Modeling LSS dynamics in 1-g laboratories has always been a major impediment not only to understanding their behavior in orbit, but also to controlling it. In cases where the theoretical model is not confirmed, current methods provide few clues concerning additional dynamical relationships that are not included in the theoretical models. CVA needs no a priori model data, or structure; all statistically significant dynamical states are determined using natural, entropy-based methods. Heretofore, a major limitation in applying adaptive

  9. Adaptive Neuro-fuzzy approach in friction identification

    NASA Astrophysics Data System (ADS)

    Zaiyad Muda @ Ismail, Muhammad

    2016-05-01

    Friction is known to affect the performance of motion control system, especially in terms of its accuracy. Therefore, a number of techniques or methods have been explored and implemented to alleviate the effects of friction. In this project, the Artificial Intelligent (AI) approach is used to model the friction which will be then used to compensate the friction. The Adaptive Neuro-Fuzzy Inference System (ANFIS) is chosen among several other AI methods because of its reliability and capabilities of solving complex computation. ANFIS is a hybrid AI-paradigm that combines the best features of neural network and fuzzy logic. This AI method (ANFIS) is effective for nonlinear system identification and compensation and thus, being used in this project.

  10. Repeated-drive adaptive feedback identification of network topologies.

    PubMed

    Yang, Pu; Zheng, Zhigang

    2014-11-01

    The identification of the topological structures of complex networks from dynamical information is a significant inverse problem. How to infer the information of network topology from short-time dynamical data is a challenging topic. The presence of synchronization among nodes makes the identification of network topology difficult. In this paper we present an efficient method called the repeated-drive adaptive feedback scheme to reveal the network connectivity from short-time dynamics. By applying the short asynchronous transient data as a repeated drive, the adjacency matrix can be successfully determined in terms of the modified adaptive feedback scheme. This improved scheme is valid for both synchronous and asynchronous cases of the network and is especially efficient in the presence of global or local synchronization, where the transient drive can be obtained by perturbing the system to get a very short asynchronous transient. The detection speed of our scheme exhibits the optimized effect by adjusting the time-series segment length and the coupling strength among nodes in the network.

  11. Heat Transfer Parametric System Identification

    DTIC Science & Technology

    1993-06-01

    Transfer Parametric System Identification 6. AUTHOR(S Parker, Gregory K. 7. PERFORMING ORGANIZATION NAME(S) AND AOORESS(ES) 8. PERFORMING ORGANIZATION...distribution is unlimited. Heat Transfer Parametric System Identification by Gregory K. Parker Lieutenant, United States Navy BS., DeVry Institute of...Modeling Concept ........ ........... 3 2. Lumped Parameter Approach ...... ......... 4 3. Parametric System Identification ....... 4 B. BASIC MODELING

  12. Sloshing II - system identification.

    NASA Astrophysics Data System (ADS)

    Ishizaki, H.; Suzuki, S.; Mikami, Y.; Takahashi, R.; Matsuda, K.

    1995-11-01

    The forced oscillation of a liquid in a cylindrical vessel is investigated. The authors mean that system identification are determination of the model parameters for the system from measurement data. The system is a mercury basin to be used for calibrating the astronomical zenith for the Photoelectric Meridian Circle (PMC). The analytic model is the long wave with correction term for viscosity. The oscillation is transmitted from the pier of PMC to the mercury. The frequency response characteristics of the sloshing amplitude and phase were experimentally obtained by the cross spectrum method. The authors identified the frequency response as the transfer function of the analytical model.

  13. Adaptive control of linearizable systems

    NASA Technical Reports Server (NTRS)

    Sastry, S. Shankar; Isidori, Alberto

    1989-01-01

    Initial results are reported regarding the adaptive control of minimum-phase nonlinear systems which are exactly input-output linearizable by state feedback. Parameter adaptation is used as a technique to make robust the exact cancellation of nonlinear terms, which is called for in the linearization technique. The application of the adaptive technique to control of robot manipulators is discussed. Only the continuous-time case is considered; extensions to the discrete-time and sampled-data cases are not obvious.

  14. Natural frequency identification of smart washer by using adaptive observer

    NASA Astrophysics Data System (ADS)

    Ito, Hitoshi; Okugawa, Masayuki

    2014-04-01

    Bolted joints are used in many machines/structures and some of them have been loosened during long time use, and unluckily these bolt loosening may cause a great accident of machines/structures system. These bolted joint, especially in important places, are main object of maintenance inspection. Maintenance inspection with human- involvement is desired to be improved owing to time-consuming, labor-intensive and high-cost. By remote and full automation monitoring of the bolt loosening, constantly monitoring of bolted joint is achieved. In order to detect loosening of bolted joints without human-involvement, applying a structural health monitoring technique and smart structures/materials concept is the key objective. In this study, a new method of bolt loosening detection by adopting a smart washer has been proposed, and the basic detection principle was discussed with numerical analysis about frequency equation of the system, was confirmed experimentally. The smart washer used in this study is in cantilever type with piezoelectric material, which adds the washer the self-sensing and actuation function. The principle used to detect the loosening of the bolts is a method of a bolt loosening detection noted that the natural frequency of a smart washer system is decreasing by the change of the bolt tightening axial tension. The feature of this proposed method is achieving to identify the natural frequency at current condition on demand by adopting the self-sensing and actuation function and system identification algorithm for varying the natural frequency depending the bolt tightening axial tension. A novel bolt loosening detection method by adopting adaptive observer is proposed in this paper. The numerical simulations are performed to verify the possibility of the adaptive observer-based loosening detection. Improvement of the detection accuracy for a bolt loosening is confirmed by adopting initial parameter and variable adaptive gain by numerical simulation.

  15. Adaptive protection algorithm and system

    DOEpatents

    Hedrick, Paul [Pittsburgh, PA; Toms, Helen L [Irwin, PA; Miller, Roger M [Mars, PA

    2009-04-28

    An adaptive protection algorithm and system for protecting electrical distribution systems traces the flow of power through a distribution system, assigns a value (or rank) to each circuit breaker in the system and then determines the appropriate trip set points based on the assigned rank.

  16. On-line physical parameter identification and adaptive control of a launch vehicle

    NASA Astrophysics Data System (ADS)

    Keller, Brian Scott

    Physical parameter identification is useful in many applications, especially in aerospace where much analysis goes into developing accurate physical system models for control. A number of off-line physical parameter identification methods exist; however, the choice of on-line methods is more limited. On-line identification methods are required for adaptive control. New on-line physical parameter identification methods are developed in this work as motivated by the problem of launch vehicle adaptive control. Launch vehicles vary from launch to launch due to differences in payloads and fuel loading. Based on the known variations, launch vehicle control laws are reanalyzed and modified if necessary; this process is expensive and adds to recurring launch vehicle costs. This reanalysis is performed despite the fact that changes in the launch vehicle are relatively minor. A trustworthy adaptive control system could eliminate this expensive redesign cycle. An adaptive control system could also provide better performance than a controller redesigned off-line. However, adaptive control is still considered too risky to use with unstable systems, primarily due to limitations in the identification methods currently available for use in adaptive control. This problem is addressed with the development of new identification algorithms. A philosophy of identification is described which uses physical parameters for identification. A technique is developed to convert existing on-line methods to a form capable of identifying physical parameters. New methods include physical parameter versions of normalized least mean squares (NLMS), research least squares (RLS), extended least squares (ELS), recursive maximum likelihood (RML), and the extended Kalman filter (EKF). Compared to transfer function identification, physical parameter identification reduces the order of the problem and speeds up convergence. Compared to the extended Kalman filter, the new methods have a faster iteration

  17. Adaptive security systems -- Combining expert systems with adaptive technologies

    SciTech Connect

    Argo, P.; Loveland, R.; Anderson, K.

    1997-09-01

    The Adaptive Multisensor Integrated Security System (AMISS) uses a variety of computational intelligence techniques to reason from raw sensor data through an array of processing layers to arrive at an assessment for alarm/alert conditions based on human behavior within a secure facility. In this paper, the authors give an overview of the system and briefly describe some of the major components of the system. This system is currently under development and testing in a realistic facility setting.

  18. Adaptive ophthalmologic system

    DOEpatents

    Olivier, Scot S.; Thompson, Charles A.; Bauman, Brian J.; Jones, Steve M.; Gavel, Don T.; Awwal, Abdul A.; Eisenbies, Stephen K.; Haney, Steven J.

    2007-03-27

    A system for improving vision that can diagnose monochromatic aberrations within a subject's eyes, apply the wavefront correction, and then enable the patient to view the results of the correction. The system utilizes a laser for producing a beam of light; a corrector; a wavefront sensor; a testing unit; an optic device for directing the beam of light to the corrector, to the retina, from the retina to the wavefront sensor, and to the testing unit; and a computer operatively connected to the wavefront sensor and the corrector.

  19. Linear system identification - The application of Lion's identification scheme to a third order system with noisy input-output measurements

    NASA Technical Reports Server (NTRS)

    Brown, C. M., Jr.; Monopoli, R. V.

    1974-01-01

    A linear system identification technique developed by Lion is adapted for use on a third-order system with six unknown parameters and noisy input-output measurements. A digital computer is employed so that rapid identification takes place with only two state variable filters. Bias in the parameter estimates is partially eliminated by a signal-to-noise ratio testing procedure.

  20. Adaptive Production Systems

    DTIC Science & Technology

    1974-12-01

    Melton, A. W., and Marton. E. (Eds.). Coding Processes in Human Memory, Washington, DC , Winston and Sons, 1972. Newell. A. Production systems...STM (1 A ’) (ACTION (USED) (DEP (NEXT B))) (B ?) (LOC A) (A ?) (B ?) ( SEPIc ’ fiAB) 16 TRUE IN PS STM (NEXT A) (1 A?) (ACTION (USED) (DEP (NEXT B

  1. Adaptive Instructional Systems

    DTIC Science & Technology

    2005-09-01

    planning stage, which used the infbrmation obtained from the Phase I research to develop a plan for utilizing the tecnolog in the proposed system. 1.4...categories of physical stimuli are perceptual, intake, time, and mobility . 01ly one of these factors, perceptual, cam be taken into account in the simulator

  2. [Health: an adaptive complex system].

    PubMed

    Toro-Palacio, Luis Fernando; Ochoa-Jaramillo, Francisco Luis

    2012-02-01

    This article points out the enormous gap that exists between complex thinking of an intellectual nature currently present in our environment, and complex experimental thinking that has facilitated the scientific and technological advances that have radically changed the world. The article suggests that life, human beings, global society, and all that constitutes health be considered as adaptive complex systems. This idea, in turn, prioritizes the adoption of a different approach that seeks to expand understanding. When this rationale is recognized, the principal characteristics and emerging properties of health as an adaptive complex system are sustained, following a care and services delivery model. Finally, some pertinent questions from this perspective are put forward in terms of research, and a series of appraisals are expressed that will hopefully serve to help us understand all that we have become as individuals and as a species. The article proposes that the delivery of health care services be regarded as an adaptive complex system.

  3. Remote Adaptive Communication System

    DTIC Science & Technology

    2001-10-25

    manage several different devices using the software tool A. Client/Server Architecture The architecture we are proposing is based on the Client...communication". International Telemedicine. Julio 1999. Pp 4. [17] F. Fernández, L. Roa, "Communication System Based on a New Open Architecture...Toledo, " Fundamentos de Neurología para educadores". IDEO. Sevilla 1994. [21] P. Coad, E. Yourdon, "Object Oriented Analysis". Yourdon Press

  4. Nanosatellite Launch Adapter System (NLAS)

    NASA Technical Reports Server (NTRS)

    Yost, Bruce D.; Hines, John W.; Agasid, Elwood F.; Buckley, Steven J.

    2010-01-01

    The utility of small spacecraft based on the University cubesat standard is becoming evident as more and more agencies and organizations are launching or planning to include nanosatellites in their mission portfolios. Cubesats are typically launched as secondary spacecraft in enclosed, containerized deployers such as the CalPoly Poly Picosat Orbital Deployer (P-POD) system. The P-POD allows for ease of integration and significantly reduces the risk exposure to the primary spacecraft and mission. NASA/ARC and the Operationally Responsive Space office are collaborating to develop a Nanosatellite Launch Adapter System (NLAS), which can accommodate multiple cubesat or cubesat-derived spacecraft on a single launch vehicle. NLAS is composed of the adapter structure, P-POD or similar spacecraft dispensers, and a sequencer/deployer system. This paper describes the NLAS system and it s future capabilities, and also provides status on the system s development and potential first use in space.

  5. Architecture for Adaptive Intelligent Systems

    NASA Technical Reports Server (NTRS)

    Hayes-Roth, Barbara

    1993-01-01

    We identify a class of niches to be occupied by 'adaptive intelligent systems (AISs)'. In contrast with niches occupied by typical AI agents, AIS niches present situations that vary dynamically along several key dimensions: different combinations of required tasks, different configurations of available resources, contextual conditions ranging from benign to stressful, and different performance criteria. We present a small class hierarchy of AIS niches that exhibit these dimensions of variability and describe a particular AIS niche, ICU (intensive care unit) patient monitoring, which we use for illustration throughout the paper. We have designed and implemented an agent architecture that supports all of different kinds of adaptation by exploiting a single underlying theoretical concept: An agent dynamically constructs explicit control plans to guide its choices among situation-triggered behaviors. We illustrate the architecture and its support for adaptation with examples from Guardian, an experimental agent for ICU monitoring.

  6. The Limits to Adaptation; A Systems Approach

    EPA Science Inventory

    The Limits to Adaptation: A Systems Approach. The ability to adapt to climate change is delineated by capacity thresholds, after which climate damages begin to overwhelm the adaptation response. Such thresholds depend upon physical properties (natural processes and engineering...

  7. Parameter testing for lattice filter based adaptive modal control systems

    NASA Technical Reports Server (NTRS)

    Sundararajan, N.; Williams, J. P.; Montgomery, R. C.

    1983-01-01

    For Large Space Structures (LSS), an adaptive control system is highly desirable. The present investigation is concerned with an 'indirect' adaptive control scheme wherein the system order, mode shapes, and modal amplitudes are estimated on-line using an identification scheme based on recursive, least-squares, lattice filters. Using the identified model parameters, a modal control law based on a pole-placement scheme with the objective of vibration suppression is employed. A method is presented for closed loop adaptive control of a flexible free-free beam. The adaptive control scheme consists of a two stage identification scheme working in series and a modal pole placement control scheme. The main conclusion from the current study is that the identified parameters cannot be directly used for controller design purposes.

  8. Making Intelligent Systems Adaptive. (Revision)

    DTIC Science & Technology

    1988-10-01

    eventually produce solutions. BY contrast, human beinge and other intelligent animls continuously adapt to the demands and opportunities presented by a...such as monitoring critically ill medical patients or controlling a manufacturing process. Following the model set by human intelligence, we define...signs probabilistically, using a belief network, as well as from first principles, using explicit models of system structure and function. Concurrent

  9. System identification techniques for helicopter higher harmonic control

    NASA Technical Reports Server (NTRS)

    Jacklin, S. A.

    1986-01-01

    This paper presents and compares several system identification techniques proposed for use with higher harmonic control algorithms designed to alleviate helicopter vibration. All method for actively controlling helicopter vibration require the knowledge of how the vibration outputs are related to the control inputs. Off-line or batch identification methods for obtaining this knowledge are presented first. Then the more advanced, adaptive identification techniques proposed to track the helicopter model parameters in flight are discussed. Considerations regarding system identifiability, identification algorithm stability, and computer implementation are also discussed.

  10. Certification Considerations for Adaptive Systems

    NASA Technical Reports Server (NTRS)

    Bhattacharyya, Siddhartha; Cofer, Darren; Musliner, David J.; Mueller, Joseph; Engstrom, Eric

    2015-01-01

    Advanced capabilities planned for the next generation of aircraft, including those that will operate within the Next Generation Air Transportation System (NextGen), will necessarily include complex new algorithms and non-traditional software elements. These aircraft will likely incorporate adaptive control algorithms that will provide enhanced safety, autonomy, and robustness during adverse conditions. Unmanned aircraft will operate alongside manned aircraft in the National Airspace (NAS), with intelligent software performing the high-level decision-making functions normally performed by human pilots. Even human-piloted aircraft will necessarily include more autonomy. However, there are serious barriers to the deployment of new capabilities, especially for those based upon software including adaptive control (AC) and artificial intelligence (AI) algorithms. Current civil aviation certification processes are based on the idea that the correct behavior of a system must be completely specified and verified prior to operation. This report by Rockwell Collins and SIFT documents our comprehensive study of the state of the art in intelligent and adaptive algorithms for the civil aviation domain, categorizing the approaches used and identifying gaps and challenges associated with certification of each approach.

  11. Adaptive Behaviour Assessment System: Indigenous Australian Adaptation Model (ABAS: IAAM)

    ERIC Educational Resources Information Center

    du Plessis, Santie

    2015-01-01

    The study objectives were to develop, trial and evaluate a cross-cultural adaptation of the Adaptive Behavior Assessment System-Second Edition Teacher Form (ABAS-II TF) ages 5-21 for use with Indigenous Australian students ages 5-14. This study introduced a multiphase mixed-method design with semi-structured and informal interviews, school…

  12. The ERIS adaptive optics system

    NASA Astrophysics Data System (ADS)

    Marchetti, Enrico; Fedrigo, Enrico; Le Louarn, Miska; Madec, Pierre-Yves; Soenke, Christian; Brast, Roland; Conzelmann, Ralf; Delabre, Bernard; Duchateau, Michel; Frank, Christoph; Klein, Barbara; Amico, Paola; Hubin, Norbert; Esposito, Simone; Antichi, Jacopo; Carbonaro, Luca; Puglisi, Alfio; Quirós-Pacheco, Fernando; Riccardi, Armando; Xompero, Marco

    2014-07-01

    The Enhanced Resolution Imager and Spectrograph (ERIS) is the new Adaptive Optics based instrument for ESO's VLT aiming at replacing NACO and SINFONI to form a single compact facility with AO fed imaging and integral field unit spectroscopic scientific channels. ERIS completes the instrument suite at the VLT adaptive telescope. In particular it is equipped with a versatile AO system that delivers up to 95% Strehl correction in K band for science observations up to 5 micron It comprises high order NGS and LGS correction enabling the observation from exoplanets to distant galaxies with a large sky coverage thanks to the coupling of the LGS WFS with the high sensitivity of its visible WFS and the capability to observe in dust embedded environment thanks to its IR low order WFS. ERIS will be installed at the Cassegrain focus of the VLT unit hosting the Adaptive Optics Facility (AOF). The wavefront correction is provided by the AOF deformable secondary mirror while the Laser Guide Star is provided by one of the four launch units of the 4 Laser Guide Star Facility for the AOF. The overall layout of the ERIS AO system is extremely compact and highly optimized: the SPIFFI spectrograph is fed directly by the Cassegrain focus and both the NIX's (IR imager) and SPIFFI's entrance windows work as visible/infrared dichroics. In this paper we describe the concept of the ERIS AO system in detail, starting from the requirements and going through the estimated performance, the opto-mechanical design and the Real-Time Computer design.

  13. ERIS adaptive optics system design

    NASA Astrophysics Data System (ADS)

    Marchetti, Enrico; Le Louarn, Miska; Soenke, Christian; Fedrigo, Enrico; Madec, Pierre-Yves; Hubin, Norbert

    2012-07-01

    The Enhanced Resolution Imager and Spectrograph (ERIS) is the next-generation instrument planned for the Very Large Telescope (VLT) and the Adaptive Optics facility (AOF). It is an AO assisted instrument that will make use of the Deformable Secondary Mirror and the new Laser Guide Star Facility (4LGSF), and it is planned for the Cassegrain focus of the telescope UT4. The project is currently in its Phase A awaiting for approval to continue to the next phases. The Adaptive Optics system of ERIS will include two wavefront sensors (WFS) to maximize the coverage of the proposed sciences cases. The first is a high order 40x40 Pyramid WFS (PWFS) for on axis Natural Guide Star (NGS) observations. The second is a high order 40x40 Shack-Hartmann WFS for single Laser Guide Stars (LGS) observations. The PWFS, with appropriate sub-aperture binning, will serve also as low order NGS WFS in support to the LGS mode with a field of view patrolling capability of 2 arcmin diameter. Both WFSs will be equipped with the very low read-out noise CCD220 based camera developed for the AOF. The real-time reconstruction and control is provided by a SPARTA real-time platform adapted to support both WFS modes. In this paper we will present the ERIS AO system in all its main aspects: opto-mechanical design, real-time computer design, control and calibrations strategy. Particular emphasis will be given to the system performance obtained via dedicated numerical simulations.

  14. Parametric Identification of Systems Via Linear Operators.

    DTIC Science & Technology

    1978-09-01

    A general parametric identification /approximation model is developed for the black box identification of linear time invariant systems in terms of... parametric identification techniques derive from the general model as special cases associated with a particular linear operator. Some possible

  15. Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

    NASA Technical Reports Server (NTRS)

    Hageman, Jacob J.; Smith, Mark S.; Stachowiak, Susan

    2003-01-01

    An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.

  16. Adaptable state based control system

    NASA Technical Reports Server (NTRS)

    Rasmussen, Robert D. (Inventor); Dvorak, Daniel L. (Inventor); Gostelow, Kim P. (Inventor); Starbird, Thomas W. (Inventor); Gat, Erann (Inventor); Chien, Steve Ankuo (Inventor); Keller, Robert M. (Inventor)

    2004-01-01

    An autonomous controller, comprised of a state knowledge manager, a control executor, hardware proxies and a statistical estimator collaborates with a goal elaborator, with which it shares common models of the behavior of the system and the controller. The elaborator uses the common models to generate from temporally indeterminate sets of goals, executable goals to be executed by the controller. The controller may be updated to operate in a different system or environment than that for which it was originally designed by the replacement of shared statistical models and by the instantiation of a new set of state variable objects derived from a state variable class. The adaptation of the controller does not require substantial modification of the goal elaborator for its application to the new system or environment.

  17. Systems identification - reprise and projections

    NASA Technical Reports Server (NTRS)

    Taylor, L. W., Jr.

    1974-01-01

    A state-of-the-arts review is given for the field of system identification. Progress in the field is traced from the early models of dynamic systems by Sir Isaac Newton up to the present day use of advanced techniques for numerous applications.

  18. Identification and dual adaptive control of a turbojet engine

    NASA Technical Reports Server (NTRS)

    Merrill, W.; Leininger, G.

    1979-01-01

    The objective of this paper is to utilize the design methods of modern control theory to realize a dual-adaptive feedback control unit for a highly nonlinear single spool airbreathing turbojet engine. Using a very detailed and accurate simulation of the nonlinear engine as the data source, linear operating point models of unspecified dimension are identified. Feedback control laws are designed at each operating point for a prespecified set of sampling rates using sampled-data output regulator theory. The control system sampling rate is determined by an adaptive sampling algorithm in correspondence with turbojet engine performance. The result is a dual-adaptive control law that is functionally dependent upon the sampling rate selected and environmental operating conditions. Simulation transients demonstrate the utility of the dual-adaptive design to improve on-board computer utilization while maintaining acceptable levels of engine performance.

  19. Adaptive diagnosis of the bilinear mechanical systems

    NASA Astrophysics Data System (ADS)

    Gelman, L.; Gorpinich, S.; Thompson, C.

    2009-07-01

    A generic adaptive approach is proposed for diagnosis of the bilinear mechanical systems. The approach adapts the free oscillation method for bilinearity diagnosis of mechanical systems. The expediency of the adaptation is proved for a recognition feature, the decrement of the free oscillations. The developed adaptation consists of variation of the adaptive likelihood ratio of the decrement with variation of the resonance frequency of the bilinear system. It is shown that in the cases of the frequency-independent and the frequency-dependent internal damping, the adaptation is expedient. To investigate effectiveness of the adaptation in these cases, a numerical simulation was carried out. The simulation results show that use of the adaptation increases the total probability of the correct diagnosis of system bilinearity.

  20. Emergent system identification using particle swarm optimization

    NASA Astrophysics Data System (ADS)

    Voss, Mark S.; Feng, Xin

    2001-10-01

    Complex Adaptive Structures can be viewed as a combination of Complex Adaptive Systems and fully integrated autonomous Smart Structures. Traditionally when designing a structure, one combines rules of thumb with theoretical results to develop an acceptable solution. This methodology will have to be extended for Complex Adaptive Structures, since they, by definition, will participate in their own design. In this paper we introduce a new methodology for Emergent System Identification that is concerned with combining the methodologies of self-organizing functional networks (GMDH - Alexy G. Ivakhnenko), Particle Swarm Optimization (PSO - James Kennedy and Russell C. Eberhart) and Genetic Programming (GP - John Koza). This paper will concentrate on the utilization of Particle Swarm Optimization in this effort and discuss how Particle Swarm Optimization relates to our ultimate goal of emergent self-organizing functional networks that can be used to identify overlapping internal structural models. The ability for Complex Adaptive Structures to identify emerging internal models will be a key component for their success.

  1. Automated drug identification system

    NASA Technical Reports Server (NTRS)

    Campen, C. F., Jr.

    1974-01-01

    System speeds up analysis of blood and urine and is capable of identifying 100 commonly abused drugs. System includes computer that controls entire analytical process by ordering various steps in specific sequences. Computer processes data output and has readout of identified drugs.

  2. Towards the identification of the loci of adaptive evolution

    PubMed Central

    Pardo-Diaz, Carolina; Salazar, Camilo; Jiggins, Chris D

    2015-01-01

    1. Establishing the genetic and molecular basis underlying adaptive traits is one of the major goals of evolutionary geneticists in order to understand the connection between genotype and phenotype and elucidate the mechanisms of evolutionary change. Despite considerable effort to address this question, there remain relatively few systems in which the genes shaping adaptations have been identified. 2. Here, we review the experimental tools that have been applied to document the molecular basis underlying evolution in several natural systems, in order to highlight their benefits, limitations and suitability. In most cases, a combination of DNA, RNA and functional methodologies with field experiments will be needed to uncover the genes and mechanisms shaping adaptation in nature. PMID:25937885

  3. QUASILINEARIZATION, SYSTEM IDENTIFICATION, AND PREDICTION

    DTIC Science & Technology

    regime in an effort to improve the quality of the control exerted. A mathematical formulation and computational solution of the problems of system ... identification and the determination of unmeasurable state variables on the basis of observations of a process, two topics of central importance in the

  4. Fast Source Camera Identification Using Content Adaptive Guided Image Filter.

    PubMed

    Zeng, Hui; Kang, Xiangui

    2016-03-01

    Source camera identification (SCI) is an important topic in image forensics. One of the most effective fingerprints for linking an image to its source camera is the sensor pattern noise, which is estimated as the difference between the content and its denoised version. It is widely believed that the performance of the sensor-based SCI heavily relies on the denoising filter used. This study proposes a novel sensor-based SCI method using content adaptive guided image filter (CAGIF). Thanks to the low complexity nature of the CAGIF, the proposed method is much faster than the state-of-the-art methods, which is a big advantage considering the potential real-time application of SCI. Despite the advantage of speed, experimental results also show that the proposed method can achieve comparable or better performance than the state-of-the-art methods in terms of accuracy.

  5. Identification and dual adaptive control of a turbojet engine

    NASA Technical Reports Server (NTRS)

    Merrill, W.; Leininger, G.

    1979-01-01

    The objective of this paper is to utilize the design methods of modern control theory to realize a 'dual-adaptive' feedback control unit for a highly non-linear single spool airbreathing turbojet engine. Using a very detailed and accurate simulation of the non-linear engine as the data source, linear operating point models of unspecified dimension are identified. Feedback control laws are designed at each operating point for a prespecified set of sampling rates using sampled-data output regulator theory. The control system sampling rate is determined by an adaptive sampling algorithm in correspondence with turbojet engine performance. The result is a 'dual-adpative' control law that is functionally dependent upon the sampling rate selected and environmental operating conditions. Simulation transients demonstrate the utility of the dual-adaptive design to improve on-board computer utilization while maintaining acceptable levels of engine performance.

  6. Adaptive identification and interpretation of pressure transient tests of horizontal wells: challenges and perspectives

    NASA Astrophysics Data System (ADS)

    Sergeev, V. L.; Van Hoang, Dong

    2016-09-01

    The paper deals with a topical issue of defining oil reservoir properties during transient tests of horizontal wells equipped with information-measuring systems and reducing well downtime. The aim is to consider challenges and perspectives of developing models and algorithms for adaptive identification and interpretation of transient tests in horizontal wells with pressure buildup curve analysis. The models and algorithms should allow analyzing flow behavior, defining oil reservoir properties and determining well test completion time, as well as reducing well downtime. The present paper is based on the previous theoretical and practical findings in the spheres of transient well testing, systems analysis, system identification, function optimization and linear algebra. Field data and results of transient well tests with pressure buildup curve analysis have also been considered. The suggested models and algorithms for adaptive interpretation of transient tests conducted in horizontal wells with resulting pressure buildup curve make it possible to analyze flow behavior, as well as define the reservoir properties and determine well test completion time. The algorithms for adaptive interpretation are based on the integrated system of radial flow PBC models with time- dependent variables, account of additional a priori information and estimates of radial flow permeability. Optimization problems are solved with the case study of PBC interpretation for five horizontal wells of the Verkhnechonsk field.

  7. Is Echo a complex adaptive system?

    PubMed

    Smith, R M; Bedau, M A

    2000-01-01

    We evaluate whether John Holland's Echo model exemplifies his theory of complex adaptive systems. After reviewing Holland's theory of complex adaptive systems and describing his Escho model, we describe and explain the characteristic evolutionary behavior observed in a series of Echo model runs. We conclude that Echo lacks the diversity of hierarchically organized aggregates that typify complex adaptive systems, and we explore possible explanations for this failure.

  8. Structural Aspects of System Identification

    NASA Technical Reports Server (NTRS)

    Glover, Keith

    1973-01-01

    The problem of identifying linear dynamical systems is studied by considering structural and deterministic properties of linear systems that have an impact on stochastic identification algorithms. In particular considered is parametrization of linear systems so that there is a unique solution and all systems in appropriate class can be represented. It is assumed that a parametrization of system matrices has been established from a priori knowledge of the system, and the question is considered of when the unknown parameters of this system can be identified from input/output observations. It is assumed that the transfer function can be asymptotically identified, and the conditions are derived for the local, global and partial identifiability of the parametrization. Then it is shown that, with the right formulation, identifiability in the presence of feedback can be treated in the same way. Similarly the identifiability of parametrizations of systems driven by unobserved white noise is considered using the results from the theory of spectral factorization.

  9. Real-time Algorithms for Sparse Neuronal System Identification.

    PubMed

    Sheikhattar, Alireza; Babadi, Behtash

    2016-08-01

    We consider the problem of sparse adaptive neuronal system identification, where the goal is to estimate the sparse time-varying neuronal model parameters in an online fashion from neural spiking observations. We develop two adaptive filters based on greedy estimation techniques and regularized log-likelihood maximization. We apply the proposed algorithms to simulated spiking data as well as experimentally recorded data from the ferret's primary auditory cortex during performance of auditory tasks. Our results reveal significant performance gains achieved by the proposed algorithms in terms of sparse identification and trackability, compared to existing algorithms.

  10. [Adaptation of the avidin-biotin system for identifying and quantifying Sendai virus antigens].

    PubMed

    Popa, L M; Marcheş, F; Repanovici, R; Iliescu, R; Muţiu, A; Cajal, N

    1989-01-01

    The avidin-biotin system was adapted in view of the identification and dosage of the Sendai parainfluenza virus and of its antigens, using the method of double antibodies (biotinylated and nonbiotinylated) in ELISA type tests.

  11. On-Orbit System Identification

    NASA Technical Reports Server (NTRS)

    Mettler, E.; Milman, M. H.; Bayard, D.; Eldred, D. B.

    1987-01-01

    Information derived from accelerometer readings benefits important engineering and control functions. Report discusses methodology for detection, identification, and analysis of motions within space station. Techniques of vibration and rotation analyses, control theory, statistics, filter theory, and transform methods integrated to form system for generating models and model parameters that characterize total motion of complicated space station, with respect to both control-induced and random mechanical disturbances.

  12. Structural System Identification Technology Verification

    DTIC Science & Technology

    1981-11-01

    USAAVRADCOM-TR-81-D-28Q V󈧄 ADA1091 81 LEI STRUCTURAL SYSTEM IDENTIFICATION TECHNOLOGY VERIFICATION \\ N. Giansante, A. Berman, W. o. Flannelly, E...release; distribution unlimited. Prepared for APPLIED TECHNOLOGY LABORATORY U. S. ARMY RESEARCH AND TECHNOLOGY LABORATORIES (AVRADCOM) S Fort Eustis...Va. 23604 4-J" APPLI ED TECHNOLOGY LABORATORY POSITION STATEMENT The Applied Technology Laboratory has been involved in the development of the Struc

  13. Modeling Power Systems as Complex Adaptive Systems

    SciTech Connect

    Chassin, David P.; Malard, Joel M.; Posse, Christian; Gangopadhyaya, Asim; Lu, Ning; Katipamula, Srinivas; Mallow, J V.

    2004-12-30

    Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.

  14. System Identification Tools for Control Structure Interaction

    DTIC Science & Technology

    1990-01-01

    DT! FILE COPY AL-TR-89-054 AD: 00 Final Report System Identification Tools for O for the period - September 1988 to Control Structure Interaction May...Classification) System Identification Tools for Control Structure Interaction (U) 12. PERSONAL AUTHOR(S) Kosut, Robert L.; Kabuli, Guntekin M. 13a. TYPE OF...identification, dynamics, 22 01 system identification , robustness, dynamic modeling, robust 22 02 control design, control design procedure 19. ABSTRACT

  15. Automated systems for identification of microorganisms.

    PubMed Central

    Stager, C E; Davis, J R

    1992-01-01

    Automated instruments for the identification of microorganisms were introduced into clinical microbiology laboratories in the 1970s. During the past two decades, the capabilities and performance characteristics of automated identification systems have steadily progressed and improved. This article explores the development of the various automated identification systems available in the United States and reviews their performance for identification of microorganisms. Observations regarding deficiencies and suggested improvements for these systems are provided. PMID:1498768

  16. An adaptive tracking observer for failure-detection systems

    NASA Technical Reports Server (NTRS)

    Sidar, M.

    1982-01-01

    The design problem of adaptive observers applied to linear, constant and variable parameters, multi-input, multi-output systems, is considered. It is shown that, in order to keep the observer's (or Kalman filter) false-alarm rate (FAR) under a certain specified value, it is necessary to have an acceptable proper matching between the observer (or KF) model and the system parameters. An adaptive observer algorithm is introduced in order to maintain desired system-observer model matching, despite initial mismatching and/or system parameter variations. Only a properly designed adaptive observer is able to detect abrupt changes in the system (actuator, sensor failures, etc.) with adequate reliability and FAR. Conditions for convergence for the adaptive process were obtained, leading to a simple adaptive law (algorithm) with the possibility of an a priori choice of fixed adaptive gains. Simulation results show good tracking performance with small observer output errors and accurate and fast parameter identification, in both deterministic and stochastic cases.

  17. System identification of Drosophila olfactory sensory neurons.

    PubMed

    Kim, Anmo J; Lazar, Aurel A; Slutskiy, Yevgeniy B

    2011-02-01

    , for a fixed mean of the odor waveform, independent of the stimulus contrast. This suggests that white noise system identification of Or59b OSNs only depends on the first moment of the odor concentration. Finally, by comparing the 2D Encoding Manifold and the 2D LNP model, we demonstrate that the OSN identification results depend on the particular type of the employed test odor waveforms. This suggests an adaptive neural encoding model for Or59b OSNs that changes its nonlinearity in response to the odor concentration waveforms.

  18. Autonomous Organization-Based Adaptive Information Systems

    DTIC Science & Technology

    2005-01-01

    intentional Multi - agent System (MAS) approach [10]. While these approaches are functional AIS systems, they lack the ability to reorganize and adapt...extended a multi - agent system with a self- reorganizing architecture to create an autonomous, adaptive information system. Design Our organization-based...goals. An advantage of a multi - agent system using the organization theoretic model is its extensibility. The practical, numerical limits to the

  19. Computerized Adaptive Mastery Tests as Expert Systems.

    ERIC Educational Resources Information Center

    Frick, Theodore W.

    1992-01-01

    Discussion of expert systems and computerized adaptive tests describes two versions of EXSPRT, a new approach that combines uncertain inference in expert systems with sequential probability ratio test (SPRT) stopping rules. Results of two studies comparing EXSPRT to adaptive mastery testing based on item response theory and SPRT approaches are…

  20. Adaptation with disturbance attenuation in nonlinear control systems

    SciTech Connect

    Basar, T.

    1997-12-31

    We present an optimization-based adaptive controller design for nonlinear systems exhibiting parametric as well as functional uncertainty. The approach involves the formulation of an appropriate cost functional that places positive weight on deviations from the achievement of desired objectives (such as tracking of a reference trajectory while the system exhibits good transient performance) and negative weight on the energy of the uncertainty. This cost functional also translates into a disturbance attenuation inequality which quantifies the effect of the presence of uncertainty on the desired objective, which in turn yields an interpretation for the optimizing control as one that optimally attenuates the disturbance, viewed as the collection of unknown parameters and unknown signals entering the system dynamics. In addition to this disturbance attenuation property, the controllers obtained also feature adaptation in the sense that they help with identification of the unknown parameters, even though this has not been set as the primary goal of the design. In spite of this adaptation/identification role, the controllers obtained are not of certainty-equivalent type, which means that the identification and the control phases of the design are not decoupled.

  1. Operator adaptation to changes in system reliability under adaptable automation.

    PubMed

    Chavaillaz, Alain; Sauer, Juergen

    2016-11-25

    This experiment examined how operators coped with a change in system reliability between training and testing. Forty participants were trained for 3 h on a complex process control simulation modelling six levels of automation (LOA). In training, participants either experienced a high- (100%) or low-reliability system (50%). The impact of training experience on operator behaviour was examined during a 2.5 h testing session, in which participants either experienced a high- (100%) or low-reliability system (60%). The results showed that most operators did not often switch between LOA. Most chose an LOA that relieved them of most tasks but maintained their decision authority. Training experience did not have a strong impact on the outcome measures (e.g. performance, complacency). Low system reliability led to decreased performance and self-confidence. Furthermore, complacency was observed under high system reliability. Overall, the findings suggest benefits of adaptable automation because it accommodates different operator preferences for LOA. Practitioner Summary: The present research shows that operators can adapt to changes in system reliability between training and testing sessions. Furthermore, it provides evidence that each operator has his/her preferred automation level. Since this preference varies strongly between operators, adaptable automation seems to be suitable to accommodate these large differences.

  2. Digital system identification and its application to digital flight control

    NASA Technical Reports Server (NTRS)

    Kotob, S.; Kaufman, H.

    1974-01-01

    On-line system identification of linear discrete systems for implementation in a digital adaptive flight controller is considered by the conventional extended Kalman filter and a decoupling process in which the linear state estimation problem and the linear parameter identification problem are each treated separately and alternately. Input requirements for parameter identifiability are established using the standard conditions of observability for a time variant system. Experimental results for simulated linearized lateral aircraft motion are included along with the effect of different initialization and updating procedures for the priming trajectory used by the filter.

  3. Evolutionary Adaptive Discovery of Phased Array Sensor Signal Identification

    SciTech Connect

    Timothy R. McJunkin; Milos Manic

    2011-05-01

    Tomography, used to create images of the internal properties and features of an object, from phased array ultasonics is improved through many sophisiticated methonds of post processing of data. One approach used to improve tomographic results is to prescribe the collection of more data, from different points of few so that data fusion might have a richer data set to work from. This approach can lead to rapid increase in the data needed to be stored and processed. It also does not necessarily lead to have the needed data. This article describes a novel approach to utilizing the data aquired as a basis for adapting the sensors focusing parameters to locate more precisely the features in the material: specifically, two evolutionary methods of autofocusing on a returned signal are coupled with the derivations of the forumulas for spatially locating the feature are given. Test results of the two novel methods of evolutionary based focusing (EBF) illustrate the improved signal strength and correction of the position of feature using the optimized focal timing parameters, called Focused Delay Identification (FoDI).

  4. Input-output identification of controlled discrete manufacturing systems

    NASA Astrophysics Data System (ADS)

    Estrada-Vargas, Ana Paula; López-Mellado, Ernesto; Lesage, Jean-Jacques

    2014-03-01

    The automated construction of discrete event models from observations of external system's behaviour is addressed. This problem, often referred to as system identification, allows obtaining models of ill-known (or even unknown) systems. In this article, an identification method for discrete event systems (DESs) controlled by a programmable logic controller is presented. The method allows processing a large quantity of observed long sequences of input/output signals generated by the controller and yields an interpreted Petri net model describing the closed-loop behaviour of the automated DESs. The proposed technique allows the identification of actual complex systems because it is sufficiently efficient and well adapted to cope with both the technological characteristics of industrial controllers and data collection requirements. Based on polynomial-time algorithms, the method is implemented as an efficient software tool which constructs and draws the model automatically; an overview of this tool is given through a case study dealing with an automated manufacturing system.

  5. The Limits to Adaptation: A Systems Approach

    NASA Astrophysics Data System (ADS)

    Felgenhauer, T. N.

    2013-12-01

    The ability to adapt to climate change is delineated by capacity thresholds, after which climate damages begin to overwhelm the adaptation response. Such thresholds depend upon physical properties (natural processes and engineering parameters), resource constraints (expressed through market prices), and societal preferences (from prices as well as cultural norms). Exceedance of adaptation capacity will require substitution either with other pre-existing policy responses or with new adaptation responses that have yet to be developed and tested. Previous modeling research shows that capacity limited adaptation will play a policy-significant role in future climate change decision-making. The aim of this study is to describe different types of adaptation response and climate damage systems and postulate how these systems might behave when the limits to adaptation are reached. The hypothesis is that this behavior will be governed by the characteristics and level of the adaptation limit, the shape of the damage curve in that specific damage area, and the availability of alternative adaptation responses once the threshold is passed, whether it is more of the old technology, a new response type, or a transformation of the climate damage and response system itself.

  6. An Adaptive Technique for a Redundant-Sensor Navigation System. Ph.D. Thesis

    NASA Technical Reports Server (NTRS)

    Chien, T. T.

    1972-01-01

    An on-line adaptive technique is developed to provide a self-contained redundant-sensor navigation system with a capability to utilize its full potentiality in reliability and performance. The gyro navigation system is modeled as a Gauss-Markov process, with degradation modes defined as changes in characteristics specified by parameters associated with the model. The adaptive system is formulated as a multistage stochastic process: (1) a detection system, (2) an identification system and (3) a compensation system. It is shown that the sufficient statistics for the partially observable process in the detection and identification system is the posterior measure of the state of degradation, conditioned on the measurement history.

  7. Personal identification credential system (PICS)

    NASA Astrophysics Data System (ADS)

    Pressley, Jackson R.; Cantrell, Thomas; Page, Lochlin; Cudlitz, Stephen; Higgins, Roy

    2005-03-01

    A pilot Personal Identification Credential System (PICS) has been developed and fielded. The PICS is a wireless biometric credential that interfaces with access control systems. The PICS consists of individual handheld Personal Identification Credentials (PIC), a PICS Reader located at a facility entry control point that interfaces with the facility entry control system, and a PICS Enrollment Station. In operation, an individual approaching a facility entry point in a vehicle picks up the PIC handheld unit and places a finger on its sensor. The PIC then authenticates the user and from within the vehicle initiates two-way, secure RF communication with the PICS Reader as the vehicle approaches the gate. The PICS Reader then verifies that the individual is authorized for admittance and notifies the facility gate entry control system, which informs the sentry that the request for access was successful or unsuccessful. If the request for access is unsuccessful, the gate entry control system automatically will close the gate. This sequence of events takes place while the car is moving through a normally open entry lane. The PIC is a small, handheld device which contains the biometric sensor (fingerprint sensor), wireless RF transceiver, processor, encryption and battery. The PIC may be used while traveling in a vehicle or may be used while on foot for access to a PICS controlled man gate or secure area access portal. The PIC is small enough to be carried in a shirt pocket, or it can be left in the user's vehicle. The PIC battery will power the PIC for months and is rechargeable. Up to 10 fingers may be stored in the PIC.

  8. System/observer/controller identification toolbox

    NASA Technical Reports Server (NTRS)

    Juang, Jer-Nan; Horta, Lucas G.; Phan, Minh

    1992-01-01

    System Identification is the process of constructing a mathematical model from input and output data for a system under testing, and characterizing the system uncertainties and measurement noises. The mathematical model structure can take various forms depending upon the intended use. The SYSTEM/OBSERVER/CONTROLLER IDENTIFICATION TOOLBOX (SOCIT) is a collection of functions, written in MATLAB language and expressed in M-files, that implements a variety of modern system identification techniques. For an open loop system, the central features of the SOCIT are functions for identification of a system model and its corresponding forward and backward observers directly from input and output data. The system and observers are represented by a discrete model. The identified model and observers may be used for controller design of linear systems as well as identification of modal parameters such as dampings, frequencies, and mode shapes. For a closed-loop system, an observer and its corresponding controller gain directly from input and output data.

  9. Adaptation in CRISPR-Cas Systems.

    PubMed

    Sternberg, Samuel H; Richter, Hagen; Charpentier, Emmanuelle; Qimron, Udi

    2016-03-17

    Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) proteins constitute an adaptive immune system in prokaryotes. The system preserves memories of prior infections by integrating short segments of foreign DNA, termed spacers, into the CRISPR array in a process termed adaptation. During the past 3 years, significant progress has been made on the genetic requirements and molecular mechanisms of adaptation. Here we review these recent advances, with a focus on the experimental approaches that have been developed, the insights they generated, and a proposed mechanism for self- versus non-self-discrimination during the process of spacer selection. We further describe the regulation of adaptation and the protein players involved in this fascinating process that allows bacteria and archaea to harbor adaptive immunity.

  10. Parameter identification for nonlinear aerodynamic systems

    NASA Technical Reports Server (NTRS)

    Pearson, Allan E.

    1991-01-01

    Work continues on frequency analysis for transfer function identification, both with respect to the continued development of the underlying algorithms and in the identification study of two physical systems. Some new results of a theoretical nature were recently obtained that lend further insight into the frequency domain interpretation of the research. Progress in each of those areas is summarized. Although not related to the system identification problem, some new results were obtained on the feedback stabilization of linear time lag systems.

  11. An adaptive learning control system for large flexible structures

    NASA Technical Reports Server (NTRS)

    Thau, F. E.

    1985-01-01

    The objective of the research has been to study the design of adaptive/learning control systems for the control of large flexible structures. In the first activity an adaptive/learning control methodology for flexible space structures was investigated. The approach was based on using a modal model of the flexible structure dynamics and an output-error identification scheme to identify modal parameters. In the second activity, a least-squares identification scheme was proposed for estimating both modal parameters and modal-to-actuator and modal-to-sensor shape functions. The technique was applied to experimental data obtained from the NASA Langley beam experiment. In the third activity, a separable nonlinear least-squares approach was developed for estimating the number of excited modes, shape functions, modal parameters, and modal amplitude and velocity time functions for a flexible structure. In the final research activity, a dual-adaptive control strategy was developed for regulating the modal dynamics and identifying modal parameters of a flexible structure. A min-max approach was used for finding an input to provide modal parameter identification while not exceeding reasonable bounds on modal displacement.

  12. Highly integrated digital electronic control: Digital flight control, aircraft model identification, and adaptive engine control

    NASA Technical Reports Server (NTRS)

    Baer-Riedhart, Jennifer L.; Landy, Robert J.

    1987-01-01

    The highly integrated digital electronic control (HIDEC) program at NASA Ames Research Center, Dryden Flight Research Facility is a multiphase flight research program to quantify the benefits of promising integrated control systems. McDonnell Aircraft Company is the prime contractor, with United Technologies Pratt and Whitney Aircraft, and Lear Siegler Incorporated as major subcontractors. The NASA F-15A testbed aircraft was modified by the HIDEC program by installing a digital electronic flight control system (DEFCS) and replacing the standard F100 (Arab 3) engines with F100 engine model derivative (EMD) engines equipped with digital electronic engine controls (DEEC), and integrating the DEEC's and DEFCS. The modified aircraft provides the capability for testing many integrated control modes involving the flight controls, engine controls, and inlet controls. This paper focuses on the first two phases of the HIDEC program, which are the digital flight control system/aircraft model identification (DEFCS/AMI) phase and the adaptive engine control system (ADECS) phase.

  13. Fieldable Nuclear Material Identification System

    SciTech Connect

    Radle, James E; Archer, Daniel E; Carter, Robert J; Mullens, James Allen; Mihalczo, John T; Britton Jr, Charles L; Lind, Randall F; Wright, Michael C

    2010-01-01

    The Fieldable Nuclear Material Identification System (FNMIS), funded by the NA-241 Office of Dismantlement and Transparency, provides information to determine the material attributes and identity of heavily shielded nuclear objects. This information will provide future treaty participants with verifiable information required by the treaty regime. The neutron interrogation technology uses a combination of information from induced fission neutron radiation and transmitted neutron imaging information to provide high confidence that the shielded item is consistent with the host's declaration. The combination of material identification information and the shape and configuration of the item are very difficult to spoof. When used at various points in the warhead dismantlement sequence, the information complimented by tags and seals can be used to track subassembly and piece part information as the disassembly occurs. The neutron transmission imaging has been developed during the last seven years and the signature analysis over the last several decades. The FNMIS is the culmination of the effort to put the technology in a usable configuration for potential treaty verification purposes.

  14. SYSTEM IDENTIFICATION OF SURFACE SHIP DYNAMICS.

    DTIC Science & Technology

    The feasibility of applying a Newtonian system identification technique to a nonlinear three degree of freedom system of equations describing the...steering and maneuvering of a surface ship is investigated. The input to the system identification program is provided by both analog and digital

  15. Reliability-Productivity Curve, a Tool for Adaptation Measures Identification

    NASA Astrophysics Data System (ADS)

    Chávez-Jiménez, A.; Granados, A.; Garrote, L. M.

    2015-12-01

    Due to climate change effects, water scarcity problems would intensify in several regions. These problems are going to impact negatively in the water low-priority demands, since these will be reduced in favor of those with high-priority. An example would be the reduction of agriculture water resources in favor of the urban ones. Then, it is important the evaluation of adaptation measures for a better water resources management. An important tool to face this challenge is the economic valuation of the water demands' impact within a water resources system. In agriculture this valuation is usually performed through the water productivity evaluation. The water productivity evaluation requires detailed information regarding the different crops like the applied technology, the agricultural supplies management, the water availability, etc. This is a restriction for an evaluation at basin scale due to the difficulty of gathers this level of detailed information. Besides, only the water availability is taken into account, but not the period when the water is distributed (i.e. water resources reliability). Water resources reliability is one of the most important variables in water resources management. This research proposes a methodology to determine the agriculture water productivity, using as variables the crops information, the crops price, the water resources availability, and the water resources reliability, at a basin scale. This methodology would allow identifying general water resources adaptation measures, providing the basis for further detailed studies in critical regions.

  16. System Identification of X-33 Neural Network

    NASA Technical Reports Server (NTRS)

    Aggarwal, Shiv

    2003-01-01

    Modern flight control research has improved spacecraft survivability as its goal. To this end we need to have a failure detection system on board. In case the spacecraft is performing imperfectly, reconfiguration of control is needed. For that purpose we need to have parameter identification of spacecraft dynamics. Parameter identification of a system is called system identification. We treat the system as a black box which receives some inputs that lead to some outputs. The question is: what kind of parameters for a particular black box can correlate the observed inputs and outputs? Can these parameters help us to predict the outputs for a new given set of inputs? This is the basic problem of system identification. The X33 was supposed to have the onboard capability of evaluating the current performance and if needed to take the corrective measures to adapt to desired performance. The X33 is comprised of both rocket and aircraft vehicle design characteristics and requires, in general, analytical methods for evaluating its flight performance. Its flight consists of four phases: ascent, transition, entry and TAEM (Terminal Area Energy Management). It spends about 200 seconds in ascent phase, reaching an altitude of about 180,000 feet and a speed of about 10 to 15 Mach. During the transition phase which lasts only about 30 seconds, its altitude may increase to about 190,000 feet but its speed is reduced to about 9 Mach. At the beginning of this phase, the Main Engine is Cut Off (MECO) and the control is reconfigured with the help of aerosurfaces (four elevons, two flaps and two rudders) and reaction control system (RCS). The entry phase brings down the altitude of X33 to about 90,000 feet and its speed to about Mach 3. It spends about 250 seconds in this phase. Main engine is still cut off and the vehicle is controlled by complex maneuvers of aerosurfaces. The last phase TAEM lasts for about 450 seconds and the altitude and speed, both are reduced to zero. The

  17. Adaptive, full-spectrum solar energy system

    DOEpatents

    Muhs, Jeffrey D.; Earl, Dennis D.

    2003-08-05

    An adaptive full spectrum solar energy system having at least one hybrid solar concentrator, at least one hybrid luminaire, at least one hybrid photobioreactor, and a light distribution system operably connected to each hybrid solar concentrator, each hybrid luminaire, and each hybrid photobioreactor. A lighting control system operates each component.

  18. Small scale adaptive optics experiment systems engineering

    NASA Technical Reports Server (NTRS)

    Boykin, William H.

    1993-01-01

    Assessment of the current technology relating to the laser power beaming system which in full scale is called the Beam Transmission Optical System (BTOS). Evaluation of system integration efforts are being conducted by the various government agencies and industry. Concepts are being developed for prototypes of adaptive optics for a BTOS.

  19. Adaptive Dialogue Systems for Assistive Living Environments

    ERIC Educational Resources Information Center

    Papangelis, Alexandros

    2013-01-01

    Adaptive Dialogue Systems (ADS) are intelligent systems, able to interact with users via multiple modalities, such as speech, gestures, facial expressions and others. Such systems are able to make conversation with their users, usually on a specific, narrow topic. Assistive Living Environments are environments where the users are by definition not…

  20. The Bilingual as an Adaptive System

    ERIC Educational Resources Information Center

    Green, David W.

    2002-01-01

    Dijkstra and van Heuven lucidly summarize the important research generated by the BIA model and provide an excellent case for the BIA+ model with its critical separation of the identification system from the task/decision system. A keynote article necessarily offers a selective exposition of the authors' thinking and so my remarks are an…

  1. Structural system identification of a composite shell

    SciTech Connect

    Red-Horse, J.R.; Carne, T.G.; James, G.H.; Witkowski, W.R.

    1991-01-01

    Structural system identification is undergoing a period of renewed interest. Probabilistic approaches to physical parameter identification in analysis finite element models make uncertainty in test results an important issue. In this paper, we investigate this issue with a simple, though in many ways representative, structural system. The results of two modal parameter identification techniques are compared and uncertainty estimates, both through bias and random errors, are quantified. The importance of the interaction between test and analysis is also highlighted. 25 refs.

  2. Structural system identification of a composite shell

    SciTech Connect

    Red-Horse, J.R.; Carne, T.G.; James, G.H.; Witkowski, W.R.

    1991-12-31

    Structural system identification is undergoing a period of renewed interest. Probabilistic approaches to physical parameter identification in analysis finite element models make uncertainty in test results an important issue. In this paper, we investigate this issue with a simple, though in many ways representative, structural system. The results of two modal parameter identification techniques are compared and uncertainty estimates, both through bias and random errors, are quantified. The importance of the interaction between test and analysis is also highlighted. 25 refs.

  3. A Mixture Rasch Model-Based Computerized Adaptive Test for Latent Class Identification

    ERIC Educational Resources Information Center

    Jiao, Hong; Macready, George; Liu, Junhui; Cho, Youngmi

    2012-01-01

    This study explored a computerized adaptive test delivery algorithm for latent class identification based on the mixture Rasch model. Four item selection methods based on the Kullback-Leibler (KL) information were proposed and compared with the reversed and the adaptive KL information under simulated testing conditions. When item separation was…

  4. Adaptive inverse control of linear and nonlinear systems using dynamic neural networks.

    PubMed

    Plett, G L

    2003-01-01

    In this paper, we see adaptive control as a three-part adaptive-filtering problem. First, the dynamical system we wish to control is modeled using adaptive system-identification techniques. Second, the dynamic response of the system is controlled using an adaptive feedforward controller. No direct feedback is used, except that the system output is monitored and used by an adaptive algorithm to adjust the parameters of the controller. Third, disturbance canceling is performed using an additional adaptive filter. The canceler does not affect system dynamics, but feeds back plant disturbance in a way that minimizes output disturbance power. The techniques work to control minimum-phase or nonminimum-phase, linear or nonlinear, single-input-single-output (SISO) or multiple-input-multiple-ouput (MIMO), stable or stabilized systems. Constraints may additionally be placed on control effort for a practical implementation. Simulation examples are presented to demonstrate that the proposed methods work very well.

  5. Adaptive Control for Microgravity Vibration Isolation System

    NASA Technical Reports Server (NTRS)

    Yang, Bong-Jun; Calise, Anthony J.; Craig, James I.; Whorton, Mark S.

    2005-01-01

    Most active vibration isolation systems that try to a provide quiescent acceleration environment for space science experiments have utilized linear design methods. In this paper, we address adaptive control augmentation of an existing classical controller that employs a high-gain acceleration feedback together with a low-gain position feedback to center the isolated platform. The control design feature includes parametric and dynamic uncertainties because the hardware of the isolation system is built as a payload-level isolator, and the acceleration Sensor exhibits a significant bias. A neural network is incorporated to adaptively compensate for the system uncertainties, and a high-pass filter is introduced to mitigate the effect of the measurement bias. Simulations show that the adaptive control improves the performance of the existing acceleration controller and keep the level of the isolated platform deviation to that of the existing control system.

  6. Stochastic system identification in structural dynamics

    USGS Publications Warehouse

    Safak, Erdal

    1988-01-01

    Recently, new identification methods have been developed by using the concept of optimal-recursive filtering and stochastic approximation. These methods, known as stochastic identification, are based on the statistical properties of the signal and noise, and do not require the assumptions of current methods. The criterion for stochastic system identification is that the difference between the recorded output and the output from the identified system (i.e., the residual of the identification) should be equal to white noise. In this paper, first a brief review of the theory is given. Then, an application of the method is presented by using ambient vibration data from a nine-story building.

  7. Operational Results of an Adaptive SDI System.

    ERIC Educational Resources Information Center

    Sage, C. R.; Fitzwater, D. R.

    The Ames Laboratory SDI system requires a minimum of human intervention. The adaptability of the system provides two major contributions to information dissemination. (1) The user benefits proportionately from the amount of effort he expends in setting up his profile and the diligence in sending back responses. (2) The document input has only to…

  8. The adaptive control system of acetylene generator

    NASA Astrophysics Data System (ADS)

    Kovaliuk, D. O.; Kovaliuk, Oleg; Burlibay, Aron; Gromaszek, Konrad

    2015-12-01

    The method of acetylene production in acetylene generator was analyzed. It was found that impossible to provide the desired process characteristics by the PID-controller. The adaptive control system of acetylene generator was developed. The proposed system combines the classic controller and fuzzy subsystem for controller parameters tuning.

  9. RNA viruses as complex adaptive systems.

    PubMed

    Elena, Santiago F; Sanjuán, Rafael

    2005-07-01

    RNA viruses have high mutation rates and so their populations exist as dynamic and complex mutant distributions. It has been consistently observed that when challenged with a new environment, viral populations adapt following hyperbolic-like kinetics: adaptation is initially very rapid, but then slows down as fitness reaches an asymptotic value. These adaptive dynamics have been explained in terms of populations moving towards the top of peaks on rugged fitness landscapes. Fitness fluctuations of varying magnitude are observed during adaptation. Often the presence of fluctuations in the evolution of physical systems indicates some form of self-organization, or where many components of the system are simultaneously involved. Here we analyze data from several in vitro evolution experiments carried out with vesicular stomatitis virus (VSV) looking for the signature of criticality and scaling. Long-range fitness correlations have been detected during the adaptive process. We also found that the magnitude of fitness fluctuations, far from being trivial, conform to a Weibull probability distribution function, suggesting that viral adaptation belongs to a broad category of phenomena previously documented in other fields and related with emergence.

  10. Adaptation in the auditory system: an overview.

    PubMed

    Pérez-González, David; Malmierca, Manuel S

    2014-01-01

    The early stages of the auditory system need to preserve the timing information of sounds in order to extract the basic features of acoustic stimuli. At the same time, different processes of neuronal adaptation occur at several levels to further process the auditory information. For instance, auditory nerve fiber responses already experience adaptation of their firing rates, a type of response that can be found in many other auditory nuclei and may be useful for emphasizing the onset of the stimuli. However, it is at higher levels in the auditory hierarchy where more sophisticated types of neuronal processing take place. For example, stimulus-specific adaptation, where neurons show adaptation to frequent, repetitive stimuli, but maintain their responsiveness to stimuli with different physical characteristics, thus representing a distinct kind of processing that may play a role in change and deviance detection. In the auditory cortex, adaptation takes more elaborate forms, and contributes to the processing of complex sequences, auditory scene analysis and attention. Here we review the multiple types of adaptation that occur in the auditory system, which are part of the pool of resources that the neurons employ to process the auditory scene, and are critical to a proper understanding of the neuronal mechanisms that govern auditory perception.

  11. Optimal Sensor Locations for System Identification

    DTIC Science & Technology

    1988-03-01

    Element Model . 19 3. A METHODOLOGY FOR OPTIMAL SENSOR LOCATIONS FOR PARAMETRIC IDENTIFICATION ................. 37 3.1. Introduction... parametric identification of structural systems depends on the location at which sensors are placed and data gathered, very little by way of a...picture on optimal sensor locations for parametric identification in a noisy measurement 6 z, -. -" environment. Section IV deals with an important aspect

  12. Managing adaptively for multifunctionality in agricultural systems.

    PubMed

    Hodbod, Jennifer; Barreteau, Olivier; Allen, Craig; Magda, Danièle

    2016-12-01

    The critical importance of agricultural systems for food security and as a dominant global landcover requires management that considers the full dimensions of system functions at appropriate scales, i.e. multifunctionality. We propose that adaptive management is the most suitable management approach for such goals, given its ability to reduce uncertainty over time and support multiple objectives within a system, for multiple actors. As such, adaptive management may be the most appropriate method for sustainably intensifying production whilst increasing the quantity and quality of ecosystem services. However, the current assessment of performance of agricultural systems doesn't reward ecosystem service provision. Therefore, we present an overview of the ecosystem functions agricultural systems should and could provide, coupled with a revised definition for assessing the performance of agricultural systems from a multifunctional perspective that, when all satisfied, would create adaptive agricultural systems that can increase production whilst ensuring food security and the quantity and quality of ecosystem services. The outcome of this high level of performance is the capacity to respond to multiple shocks without collapse, equity and triple bottom line sustainability. Through the assessment of case studies, we find that alternatives to industrialized agricultural systems incorporate more functional goals, but that there are mixed findings as to whether these goals translate into positive measurable outcomes. We suggest that an adaptive management perspective would support the implementation of a systematic analysis of the social, ecological and economic trade-offs occurring within such systems, particularly between ecosystem services and functions, in order to provide suitable and comparable assessments. We also identify indicators to monitor performance at multiple scales in agricultural systems which can be used within an adaptive management framework to increase

  13. The ERIS adaptive optics system

    NASA Astrophysics Data System (ADS)

    Riccardi, A.; Esposito, S.; Agapito, G.; Antichi, J.; Biliotti, V.; Blain, C.; Briguglio, R.; Busoni, L.; Carbonaro, L.; Di Rico, G.; Giordano, C.; Pinna, E.; Puglisi, A.; Spanò, P.; Xompero, M.; Baruffolo, A.; Kasper, M.; Egner, S.; Suàrez Valles, M.; Soenke, C.; Downing, M.; Reyes, J.

    2016-07-01

    ERIS is the new AO instrument for VLT-UT4 led by a Consortium of Max-Planck Institut fuer Extraterrestrische Physik, UK-ATC, ETH-Zurich, ESO and INAF. The ERIS AO system provides NGS mode to deliver high contrast correction and LGS mode to extend high Strehl performance to large sky coverage. The AO module includes NGS and LGS wavefront sensors and, with VLT-AOF Deformable Secondary Mirror and Laser Facility, will provide AO correction to the high resolution imager NIX (1-5um) and the IFU spectrograph SPIFFIER (1-2.5um). In this paper we present the preliminary design of the ERIS AO system and the estimated correction performance.

  14. Evaluation of Automated Yeast Identification System

    NASA Technical Reports Server (NTRS)

    McGinnis, M. R.

    1996-01-01

    One hundred and nine teleomorphic and anamorphic yeast isolates representing approximately 30 taxa were used to evaluate the accuracy of the Biolog yeast identification system. Isolates derived from nomenclatural types, environmental, and clinica isolates of known identity were tested in the Biolog system. Of the isolates tested, 81 were in the Biolog database. The system correctly identified 40, incorrectly identified 29, and was unable to identify 12. Of the 28 isolates not in the database, 18 were given names, whereas 10 were not. The Biolog yeast identification system is inadequate for the identification of yeasts originating from the environment during space program activities.

  15. Adaptive System Modeling for Spacecraft Simulation

    NASA Technical Reports Server (NTRS)

    Thomas, Justin

    2011-01-01

    This invention introduces a methodology and associated software tools for automatically learning spacecraft system models without any assumptions regarding system behavior. Data stream mining techniques were used to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). Evaluation on historical ISS telemetry data shows that adaptive system modeling reduces simulation error anywhere from 50 to 90 percent over existing approaches. The purpose of the methodology is to outline how someone can create accurate system models from sensor (telemetry) data. The purpose of the software is to support the methodology. The software provides analysis tools to design the adaptive models. The software also provides the algorithms to initially build system models and continuously update them from the latest streaming sensor data. The main strengths are as follows: Creates accurate spacecraft system models without in-depth system knowledge or any assumptions about system behavior. Automatically updates/calibrates system models using the latest streaming sensor data. Creates device specific models that capture the exact behavior of devices of the same type. Adapts to evolving systems. Can reduce computational complexity (faster simulations).

  16. Evolving Systems and Adaptive Key Component Control

    NASA Technical Reports Server (NTRS)

    Frost, Susan A.; Balas, Mark J.

    2009-01-01

    We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. An introduction to Evolving Systems and exploration of the essential topics of the control and stability properties of Evolving Systems is provided. This chapter defines a framework for Evolving Systems, develops theory and control solutions for fundamental characteristics of Evolving Systems, and provides illustrative examples of Evolving Systems and their control with adaptive key component controllers.

  17. Adaptive fuzzy system for 3-D vision

    NASA Technical Reports Server (NTRS)

    Mitra, Sunanda

    1993-01-01

    An adaptive fuzzy system using the concept of the Adaptive Resonance Theory (ART) type neural network architecture and incorporating fuzzy c-means (FCM) system equations for reclassification of cluster centers was developed. The Adaptive Fuzzy Leader Clustering (AFLC) architecture is a hybrid neural-fuzzy system which learns on-line in a stable and efficient manner. The system uses a control structure similar to that found in the Adaptive Resonance Theory (ART-1) network to identify the cluster centers initially. The initial classification of an input takes place in a two stage process; a simple competitive stage and a distance metric comparison stage. The cluster prototypes are then incrementally updated by relocating the centroid positions from Fuzzy c-Means (FCM) system equations for the centroids and the membership values. The operational characteristics of AFLC and the critical parameters involved in its operation are discussed. The performance of the AFLC algorithm is presented through application of the algorithm to the Anderson Iris data, and laser-luminescent fingerprint image data. The AFLC algorithm successfully classifies features extracted from real data, discrete or continuous, indicating the potential strength of this new clustering algorithm in analyzing complex data sets. The hybrid neuro-fuzzy AFLC algorithm will enhance analysis of a number of difficult recognition and control problems involved with Tethered Satellite Systems and on-orbit space shuttle attitude controller.

  18. System Identification for Nonlinear Control Using Neural Networks

    NASA Technical Reports Server (NTRS)

    Stengel, Robert F.; Linse, Dennis J.

    1990-01-01

    An approach to incorporating artificial neural networks in nonlinear, adaptive control systems is described. The controller contains three principal elements: a nonlinear inverse dynamic control law whose coefficients depend on a comprehensive model of the plant, a neural network that models system dynamics, and a state estimator whose outputs drive the control law and train the neural network. Attention is focused on the system identification task, which combines an extended Kalman filter with generalized spline function approximation. Continual learning is possible during normal operation, without taking the system off line for specialized training. Nonlinear inverse dynamic control requires smooth derivatives as well as function estimates, imposing stringent goals on the approximating technique.

  19. Adaptive synchronization and anticipatory dynamical systems

    NASA Astrophysics Data System (ADS)

    Yang, Ying-Jen; Chen, Chun-Chung; Lai, Pik-Yin; Chan, C. K.

    2015-09-01

    Many biological systems can sense periodical variations in a stimulus input and produce well-timed, anticipatory responses after the input is removed. Such systems show memory effects for retaining timing information in the stimulus and cannot be understood from traditional synchronization consideration of passive oscillatory systems. To understand this anticipatory phenomena, we consider oscillators built from excitable systems with the addition of an adaptive dynamics. With such systems, well-timed post-stimulus responses similar to those from experiments can be obtained. Furthermore, a well-known model of working memory is shown to possess similar anticipatory dynamics when the adaptive mechanism is identified with synaptic facilitation. The last finding suggests that this type of oscillator can be common in neuronal systems with plasticity.

  20. Dental orthopantomogram biometrics system for human identification.

    PubMed

    Singh, Sandeep; Bhargava, Darpan; Deshpande, Ashwini

    2013-07-01

    Fingerprinting is the most widely accepted method of identification of people. But in cases of disfigured, decomposed, burnt or fragmented bodies, it is of limited value. Teeth and dental restorations on the other hand are extremely resistant to destruction by fire. They retain a number of their original characteristics, which are often unique and hence offer a possibility of rather accurate and legally acceptable identification of such remains. This study was undertaken to evaluate the utility of orthopantomography for human identification and propose a coding system for orthopantomogram (OPG), which can be utilized as an identification tool in forensic sciences.

  1. On neural networks in identification and control of dynamic systems

    NASA Technical Reports Server (NTRS)

    Phan, Minh; Juang, Jer-Nan; Hyland, David C.

    1993-01-01

    This paper presents a discussion of the applicability of neural networks in the identification and control of dynamic systems. Emphasis is placed on the understanding of how the neural networks handle linear systems and how the new approach is related to conventional system identification and control methods. Extensions of the approach to nonlinear systems are then made. The paper explains the fundamental concepts of neural networks in their simplest terms. Among the topics discussed are feed forward and recurrent networks in relation to the standard state-space and observer models, linear and nonlinear auto-regressive models, linear, predictors, one-step ahead control, and model reference adaptive control for linear and nonlinear systems. Numerical examples are presented to illustrate the application of these important concepts.

  2. Robust adaptive control of HVDC systems

    SciTech Connect

    Reeve, J.; Sultan, M. )

    1994-07-01

    The transient performance of an HVDC power system is highly dependent on the parameters of the current/voltage regulators of the converter controls. In order to better accommodate changes in system structure or dc operating conditions, this paper introduces a new adaptive control strategy. The advantages of automatic tuning for continuous fine tuning are combined with predetermined gain scheduling in order to achieve robustness for large disturbances. Examples are provided for a digitally simulated back-to-back dc system.

  3. An adaptive learning control system for aircraft

    NASA Technical Reports Server (NTRS)

    Mekel, R.; Nachmias, S.

    1976-01-01

    A learning control system is developed which blends the gain scheduling and adaptive control into a single learning system that has the advantages of both. An important feature of the developed learning control system is its capability to adjust the gain schedule in a prescribed manner to account for changing aircraft operating characteristics. Furthermore, if tests performed by the criteria of the learning system preclude any possible change in the gain schedule, then the overall system becomes an ordinary gain scheduling system. Examples are discussed.

  4. Final Report - Regulatory Considerations for Adaptive Systems

    NASA Technical Reports Server (NTRS)

    Wilkinson, Chris; Lynch, Jonathan; Bharadwaj, Raj

    2013-01-01

    This report documents the findings of a preliminary research study into new approaches to the software design assurance of adaptive systems. We suggest a methodology to overcome the software validation and verification difficulties posed by the underlying assumption of non-adaptive software in the requirementsbased- testing verification methods in RTCA/DO-178B and C. An analysis of the relevant RTCA/DO-178B and C objectives is presented showing the reasons for the difficulties that arise in showing satisfaction of the objectives and suggested additional means by which they could be satisfied. We suggest that the software design assurance problem for adaptive systems is principally one of developing correct and complete high level requirements and system level constraints that define the necessary system functional and safety properties to assure the safe use of adaptive systems. We show how analytical techniques such as model based design, mathematical modeling and formal or formal-like methods can be used to both validate the high level functional and safety requirements, establish necessary constraints and provide the verification evidence for the satisfaction of requirements and constraints that supplements conventional testing. Finally the report identifies the follow-on research topics needed to implement this methodology.

  5. System identification as an application of optimization

    NASA Astrophysics Data System (ADS)

    Brasio, Ana S. R.; Romanenko, Andrey; Fernandes, Natercia C. P.

    2012-09-01

    The work concerns the system identification of industrial processes via the Sequential Quadratic Programming algorithm. The proposed approach, testing scenarios, and the system identification results are discussed. The tool is tested with two datasets, the first one collected in loco from an industrial process and the second one generated with a plant simulator of a continuous stirred tank reactor, a system widely used in industry. In both cases, the resulting models capture well the process dynamics.

  6. Information, Consistent Estimation and Dynamic System Identification.

    DTIC Science & Technology

    1976-11-01

    Data fnfetd) --t 90gg- I .No-ýnber 1976 Report ESL-R-718 INFORMATION, CONSISTENT ESTIMATION AND DYNAMIC SYSTEM IDENTIFICATION by Yoram Bara W This report...8217 • L .. +• " -’ .... .. .... .. .. ’• ’• "- ’"l ’"ll ~ll~ 2 l 1NFURMAT10N~, CUNSISTENT LST1IMATION JaN DYiNAMIC SYSTEM IDENTIFICATION byI Yoramn...one? 1. particular problem of considerable practical significance is that qI -3-3 of dynamic system identification . The situation described above, and

  7. An adaptive deep learning approach for PPG-based identification.

    PubMed

    Jindal, V; Birjandtalab, J; Pouyan, M Baran; Nourani, M

    2016-08-01

    Wearable biosensors have become increasingly popular in healthcare due to their capabilities for low cost and long term biosignal monitoring. This paper presents a novel two-stage technique to offer biometric identification using these biosensors through Deep Belief Networks and Restricted Boltzman Machines. Our identification approach improves robustness in current monitoring procedures within clinical, e-health and fitness environments using Photoplethysmography (PPG) signals through deep learning classification models. The approach is tested on TROIKA dataset using 10-fold cross validation and achieved an accuracy of 96.1%.

  8. Petascale IO Using The Adaptable IO System

    SciTech Connect

    Lofstead, J.; Klasky, Scott A; Abbasi, H.

    2009-01-01

    ADIOS, the adaptable IO system, has demonstrated excellent scalability to 29,000 cores. With the introduction of the XT5 upgrades to Jaguar, new optimizations are required to successfully reach 140,000+ cores. This paper explains the techniques employed and shows the performance levels attained.

  9. User Modeling in Adaptive Hypermedia Educational Systems

    ERIC Educational Resources Information Center

    Martins, Antonio Constantino; Faria, Luiz; Vaz de Carvalho, Carlos; Carrapatoso, Eurico

    2008-01-01

    This document is a survey in the research area of User Modeling (UM) for the specific field of Adaptive Learning. The aims of this document are: To define what it is a User Model; To present existing and well known User Models; To analyze the existent standards related with UM; To compare existing systems. In the scientific area of User Modeling…

  10. Adaptive control system for gas producing wells

    SciTech Connect

    Fedor, Pashchenko; Sergey, Gulyaev; Alexander, Pashchenko

    2015-03-10

    Optimal adaptive automatic control system for gas producing wells cluster is proposed intended for solving the problem of stabilization of the output gas pressure in the cluster at conditions of changing gas flow rate and changing parameters of the wells themselves, providing the maximum high resource of hardware elements of automation.

  11. An adaptive strategy for controlling chaotic system.

    PubMed

    Cao, Yi-Jia; Hang, Hong-Xian

    2003-01-01

    This paper presents an adaptive strategy for controlling chaotic systems. By employing the phase space reconstruction technique in nonlinear dynamical systems theory, the proposed strategy transforms the nonlinear system into canonical form, and employs a nonlinear observer to estimate the uncertainties and disturbances of the nonlinear system, and then establishes a state-error-like feedback law. The developed control scheme allows chaos control in spite of modeling errors and parametric variations. The effectiveness of the proposed approach has been demonstrated through its applications to two well-known chaotic systems: Duffing oscillator and Rössler chaos.

  12. Information measuring systems with mobile devices for identification of air pollution parameters caused by transport

    NASA Astrophysics Data System (ADS)

    Mokin, Vitalii B.; Goriachev, Georgii V.; Dziuniak, Dmytro Y.; Bondaletov, Konstantin O.; Zhukov, Serhii O.; Duk, Mariusz; Sailarbek, Saltanat

    2016-09-01

    The analysis of modern information measuring systems (IMS) for identification model parameters of the air pollution is carried out. That allows to increase the accuracy of this identification due to their complex application. The known model based on the fuzzy knowledge base was adapted to this task. It is specified how the offered IMS can increase the accuracy of the parameters identification. The results of the experiment with the use of the offered IMS in Vinnytsia city presented in the paper.

  13. Ethnolinguistic Identification and Adaptation of Repatriates in Polycultural Kazakhstan

    ERIC Educational Resources Information Center

    Bokayev, Baurzhan; Zharkynbekova, Sholpan; Nurseitova, Khalida; Bokayeva, Ainash; Akzhigitova, Assel; Nurgalieva, Saniya

    2012-01-01

    The issues of social, cultural, and language adjustment and the integration of repatriates into the Kazakhstani society are crucial factors in maintaining a stable society. The complicated process of self-identification of ethnic Kazakhs is a major aspect of their sociolinguistic "penetration" into Kazakh society. In this work we…

  14. Adaptable Transponder for Multiple Telemetry Systems

    NASA Technical Reports Server (NTRS)

    Sims, William Herbert, III (Inventor); Varnavas, Kosta A. (Inventor)

    2014-01-01

    The present invention is a stackable telemetry circuit board for use in telemetry systems for satellites and other purposes. The present invention incorporates previously-qualified interchangeable circuit boards, or "decks," that perform functions such as power, signal receiving and transmission, and processing. Each deck is adapted to serve a range of telemetry applications. This provides flexibility in the construction of the stackable telemetry circuit board and significantly reduces the cost and time necessary to develop a telemetry system.

  15. Adaptive P300 based control system

    PubMed Central

    Jin, Jing; Allison, Brendan Z.; Sellers, Eric W.; Brunner, Clemens; Horki, Petar; Wang, Xingyu; Neuper, Christa

    2015-01-01

    An adaptive P300 brain-computer interface (BCI) using a 12 × 7 matrix explored new paradigms to improve bit rate and accuracy. During online use, the system adaptively selects the number of flashes to average. Five different flash patterns were tested. The 19-flash paradigm represents the typical row/column presentation (i.e., 12 columns and 7 rows). The 9- and 14-flash A & B paradigms present all items of the 12 × 7 matrix three times using either nine or 14 flashes (instead of 19), decreasing the amount of time to present stimuli. Compared to 9-flash A, 9-flash B decreased the likelihood that neighboring items would flash when the target was not flashing, thereby reducing interference from items adjacent to targets. 14-flash A also reduced adjacent item interference and 14-flash B additionally eliminated successive (double) flashes of the same item. Results showed that accuracy and bit rate of the adaptive system were higher than the non-adaptive system. In addition, 9- and 14-flash B produced significantly higher performance than their respective A conditions. The results also show the trend that the 14-flash B paradigm was better than the 19-flash pattern for naïve users. PMID:21474877

  16. Adaptive functional systems: learning with chaos.

    PubMed

    Komarov, M A; Osipov, G V; Burtsev, M S

    2010-12-01

    We propose a new model of adaptive behavior that combines a winnerless competition principle and chaos to learn new functional systems. The model consists of a complex network of nonlinear dynamical elements producing sequences of goal-directed actions. Each element describes dynamics and activity of the functional system which is supposed to be a distributed set of interacting physiological elements such as nerve or muscle that cooperates to obtain certain goal at the level of the whole organism. During "normal" behavior, the dynamics of the system follows heteroclinic channels, but in the novel situation chaotic search is activated and a new channel leading to the target state is gradually created simulating the process of learning. The model was tested in single and multigoal environments and had demonstrated a good potential for generation of new adaptations.

  17. The odontology victim identification skill assessment system.

    PubMed

    Zohn, Harry K; Dashkow, Sheila; Aschheim, Kenneth W; Dobrin, Lawrence A; Glazer, Howard S; Kirschbaum, Mitchell; Levitt, Daniel; Feldman, Cecile A

    2010-05-01

    Mass fatality identification efforts involving forensic odontology can involve hundreds of dental volunteers. A literature review was conducted and forensic odontologists and dental educators consulted to identify lessons learned from past mass fatality identification efforts. As a result, the authors propose a skill assessment system, the Odontology Victim Identification Skill Assessment System (OVID-SAS), which details qualifications required to participate on the Antemortem, Postmortem, Ante/Postmortem Comparison, Field, and Shift Leader/Initial Response Teams. For each qualification, specific skills have been identified along with suggested educational pedagogy and skill assessment methods. Courses and assessments can be developed by dental schools, professional associations, or forensic organizations to teach and test for the skills required for dental volunteers to participate on each team. By implementing a system, such as OVID-SAS, forensic odontologists responsible for organizing and managing a forensic odontology mass fatality identification effort will be able to optimally utilize individuals presenting with proven skills.

  18. Adaptive Embedded Digital System for Plasma Diagnostics

    NASA Astrophysics Data System (ADS)

    González, Angel; Rodríguez, Othoniel; Mangual, Osvaldo; Ponce, Eduardo; Vélez, Xavier

    2014-05-01

    An Adaptive Embedded Digital System to perform plasma diagnostics using electrostatic probes was developed at the Plasma Engineering Laboratory at Polytechnic University of Puerto Rico. The system will replace the existing instrumentation at the Laboratory, using reconfigurable hardware to minimize the equipment and software needed to perform diagnostics. The adaptability of the design resides on the possibility of replacing the computational algorithm on the fly, allowing to use the same hardware for different probes. The system was prototyped using Very High Speed Integrated Circuits Hardware Description Language (VHDL) into an Field Programmable Gate Array (FPGA) board. The design of the Embedded Digital System includes a Zero Phase Digital Filter, a Derivative Unit, and a Computational Unit designed using the VHDL-2008 Support Library. The prototype is able to compute the Plasma Electron Temperature and Density from a Single Langmuir probe. The system was tested using real data previously acquired from a single Langmuir probe. The plasma parameters obtained from the embedded system were compared with results computed using matlab yielding excellent matching. The new embedded system operates on 4096 samples versus 500 on the previous system, and completes its computations in 26 milliseconds compared with about 15 seconds on the previous system.

  19. Almost Sure Convergence of Adaptive Identification Prediction and Control Algorithms.

    DTIC Science & Technology

    1981-03-01

    achievable with known plant parameters, in the Cesaro sense. An additional regularity assumption on the signal model establishes the result that the...the Cesaro sense. Under an additional regularity assumption, the convergence of these errors and also that of the tracking error for the adaptive con...The 4- convergence in all these references is established in the Cesaro sense. The above schemes of [7-10] leave the question unanswered as to

  20. Phase coherence adaptive processor for automatic signal detection and identification

    NASA Astrophysics Data System (ADS)

    Wagstaff, Ronald A.

    2006-05-01

    A continuously adapting acoustic signal processor with an automatic detection/decision aid is presented. Its purpose is to preserve the signals of tactical interest, and filter out other signals and noise. It utilizes single sensor or beamformed spectral data and transforms the signal and noise phase angles into "aligned phase angles" (APA). The APA increase the phase temporal coherence of signals and leave the noise incoherent. Coherence thresholds are set, which are representative of the type of source "threat vehicle" and the geographic area or volume in which it is operating. These thresholds separate signals, based on the "quality" of their APA coherence. An example is presented in which signals from a submerged source in the ocean are preserved, while clutter signals from ships and noise are entirely eliminated. Furthermore, the "signals of interest" were identified by the processor's automatic detection aid. Similar performance is expected for air and ground vehicles. The processor's equations are formulated in such a manner that they can be tuned to eliminate noise and exploit signal, based on the "quality" of their APA temporal coherence. The mathematical formulation for this processor is presented, including the method by which the processor continuously self-adapts. Results show nearly complete elimination of noise, with only the selected category of signals remaining, and accompanying enhancements in spectral and spatial resolution. In most cases, the concept of signal-to-noise ratio looses significance, and "adaptive automated /decision aid" is more relevant.

  1. Nuclear Materials Identification System Operational Manual

    SciTech Connect

    Chiang, L.G.

    2001-04-10

    This report describes the operation and setup of the Nuclear Materials Identification System (NMIS) with a {sup 252}Cf neutron source at the Oak Ridge Y-12 Plant. The components of the system are described with a description of the setup of the system along with an overview of the NMIS measurements for scanning, calibration, and confirmation of inventory items.

  2. Biological identification systems: genetic markers.

    PubMed

    Cunningham, E P; Meghen, C M

    2001-08-01

    Individual animals differ from each other on a number of biological levels. At the most basic level, the deoxyribonucleic acid (DNA) of each animal is different, and transcription of the DNA code yields variations at the protein level, which in turn give rise to individual diversity at the physical level. In recent years, accessing the primary genetic code of individual animals has become straightforward. The authors briefly review the development of biological identification technologies and then consider in more detail the application of current DNA testing technologies to issues of traceability of live animals and derived products. Although largely focused on cattle and beef traceability, the principles described are relevant to ovine, porcine and equine traceability. The accelerating pace of innovation and development within the field of molecular genetics suggests that the technologies described may soon be superseded. However, the principles of genetic identification will remain unchanged.

  3. Adaptive Optics Imaging of Solar System Objects

    NASA Technical Reports Server (NTRS)

    Roddier, Francois; Owen, Toby

    1997-01-01

    Most solar system objects have never been observed at wavelengths longer than the R band with an angular resolution better than 1 sec. The Hubble Space Telescope itself has only recently been equipped to observe in the infrared. However, because of its small diameter, the angular resolution is lower than that one can now achieved from the ground with adaptive optics, and time allocated to planetary science is limited. We have been using adaptive optics (AO) on a 4-m class telescope to obtain 0.1 sec resolution images solar system objects at far red and near infrared wavelengths (0.7-2.5 micron) which best discriminate their spectral signatures. Our efforts has been put into areas of research for which high angular resolution is essential, such as the mapping of Titan and of large asteroids, the dynamics and composition of Neptune stratospheric clouds, the infrared photometry of Pluto, Charon, and close satellites previously undetected from the ground.

  4. Demonstration of portable solar adaptive optics system

    NASA Astrophysics Data System (ADS)

    Ren, Deqing; Dong, Bing

    2012-10-01

    Solar-adaptive optics (AO) are more challenging than night-time AO, in some aspects. A portable solar adaptive optics (PSAO) system featuring compact physical size, low cost, and good performance has been proposed and developed. PSAO can serve as a visiting instrument for any existing ground-based solar telescope to improve solar image quality by replacing just a few optical components. High-level programming language, LabVIEW, is used to develop the wavefront sensing and control software, and general purpose computers are used to drive the whole system. During October 2011, the feasibility and good performance of PSAO was demonstrated with the 61-cm solar telescope at San Fernando Observatory. The image contrast and resolution are noticeably improved after AO correction.

  5. Adaptive control design for hysteretic smart systems

    NASA Astrophysics Data System (ADS)

    Fan, Xiang; Smith, Ralph C.

    2009-03-01

    Ferroelectric and ferromagnetic actuators are being considered for a range of industrial, aerospace, aeronautic and biomedical applications due to their unique transduction capabilities. However, they also exhibit hysteretic and nonlinear behavior that must be accommodated in models and control designs. If uncompensated, these effects can yield reduced system performance and, in the worst case, can produce unpredictable behavior of the control system. One technique for control design is to approximately linearize the actuator dynamics using an adaptive inverse compensator that is also able to accommodate model uncertainties and error introduced by the inverse algorithm. This paper describes the design of an adaptive inverse control technique based on the homogenized energy model for hysteresis. The resulting inverse filter is incorporated in an L1 control theory to provide a robust control algorithm capable of providing high speed, high accuracy tracking in the presence of actuator hysteresis and nonlinearities. Properties of the control design are illustrated through numerical examples.

  6. Multi-level RF identification system

    DOEpatents

    Steele, Kerry D.; Anderson, Gordon A.; Gilbert, Ronald W.

    2004-07-20

    A radio frequency identification system having a radio frequency transceiver for generating a continuous wave RF interrogation signal that impinges upon an RF identification tag. An oscillation circuit in the RF identification tag modulates the interrogation signal with a subcarrier of a predetermined frequency and modulates the frequency-modulated signal back to the transmitting interrogator. The interrogator recovers and analyzes the subcarrier signal and determines its frequency. The interrogator generates an output indicative of the frequency of the subcarrier frequency, thereby identifying the responding RFID tag as one of a "class" of RFID tags configured to respond with a subcarrier signal of a predetermined frequency.

  7. Modeling, system identification, and control of ASTREX

    NASA Technical Reports Server (NTRS)

    Abhyankar, Nandu S.; Ramakrishnan, J.; Byun, K. W.; Das, A.; Cossey, Derek F.; Berg, J.

    1993-01-01

    The modeling, system identification and controller design aspects of the ASTREX precision space structure are presented in this work. Modeling of ASTREX is performed using NASTRAN, TREETOPS and I-DEAS. The models generated range from simple linear time-invariant models to nonlinear models used for large angle simulations. Identification in both the time and frequency domains are presented. The experimental set up and the results from the identification experiments are included. Finally, controller design for ASTREX is presented. Simulation results using this optimal controller demonstrate the controller performance. Finally the future directions and plans for the facility are addressed.

  8. On Markov parameters in system identification

    NASA Technical Reports Server (NTRS)

    Phan, Minh; Juang, Jer-Nan; Longman, Richard W.

    1991-01-01

    A detailed discussion of Markov parameters in system identification is given. Different forms of input-output representation of linear discrete-time systems are reviewed and discussed. Interpretation of sampled response data as Markov parameters is presented. Relations between the state-space model and particular linear difference models via the Markov parameters are formulated. A generalization of Markov parameters to observer and Kalman filter Markov parameters for system identification is explained. These extended Markov parameters play an important role in providing not only a state-space realization, but also an observer/Kalman filter for the system of interest.

  9. Cyberspace: The Ultimate Complex Adaptive System

    DTIC Science & Technology

    2011-04-05

    capable of a transaction with a given agent; tags also facilitate the formation of aggregates , or meta-agents. Meta-agents help distrib- ute and... Mbps or Gbps through communications links Path Roads, Rails, Flight Path, Sea- lanes Links, Connections Terrain Hills, Valleys, Urban Canyons... aggregate of many factors, both local and global. Unfit agents are more likely to instigate schema change. What is a Complex Adaptive System? This

  10. Adaptable radiation monitoring system and method

    DOEpatents

    Archer, Daniel E.; Beauchamp, Brock R.; Mauger, G. Joseph; Nelson, Karl E.; Mercer, Michael B.; Pletcher, David C.; Riot, Vincent J.; Schek, James L.; Knapp, David A.

    2006-06-20

    A portable radioactive-material detection system capable of detecting radioactive sources moving at high speeds. The system has at least one radiation detector capable of detecting gamma-radiation and coupled to an MCA capable of collecting spectral data in very small time bins of less than about 150 msec. A computer processor is connected to the MCA for determining from the spectral data if a triggering event has occurred. Spectral data is stored on a data storage device, and a power source supplies power to the detection system. Various configurations of the detection system may be adaptably arranged for various radiation detection scenarios. In a preferred embodiment, the computer processor operates as a server which receives spectral data from other networked detection systems, and communicates the collected data to a central data reporting system.

  11. Investigation of the Multiple Method Adaptive Control (MMAC) method for flight control systems

    NASA Technical Reports Server (NTRS)

    Athans, M.; Baram, Y.; Castanon, D.; Dunn, K. P.; Green, C. S.; Lee, W. H.; Sandell, N. R., Jr.; Willsky, A. S.

    1979-01-01

    The stochastic adaptive control of the NASA F-8C digital-fly-by-wire aircraft using the multiple model adaptive control (MMAC) method is presented. The selection of the performance criteria for the lateral and the longitudinal dynamics, the design of the Kalman filters for different operating conditions, the identification algorithm associated with the MMAC method, the control system design, and simulation results obtained using the real time simulator of the F-8 aircraft at the NASA Langley Research Center are discussed.

  12. Gaia as a complex adaptive system.

    PubMed Central

    Lenton, Timothy M; van Oijen, Marcel

    2002-01-01

    We define the Gaia system of life and its environment on Earth, review the status of the Gaia theory, introduce potentially relevant concepts from complexity theory, then try to apply them to Gaia. We consider whether Gaia is a complex adaptive system (CAS) in terms of its behaviour and suggest that the system is self-organizing but does not reside in a critical state. Gaia has supported abundant life for most of the last 3.8 Gyr. Large perturbations have occasionally suppressed life but the system has always recovered without losing the capacity for large-scale free energy capture and recycling of essential elements. To illustrate how complexity theory can help us understand the emergence of planetary-scale order, we present a simple cellular automata (CA) model of the imaginary planet Daisyworld. This exhibits emergent self-regulation as a consequence of feedback coupling between life and its environment. Local spatial interaction, which was absent from the original model, can destabilize the system by generating bifurcation regimes. Variation and natural selection tend to remove this instability. With mutation in the model system, it exhibits self-organizing adaptive behaviour in its response to forcing. We close by suggesting how artificial life ('Alife') techniques may enable more comprehensive feasibility tests of Gaia. PMID:12079529

  13. Complex Adaptive Systems of Systems (CASOS) engineering environment.

    SciTech Connect

    Detry, Richard Joseph; Linebarger, John Michael; Finley, Patrick D.; Maffitt, S. Louise; Glass, Robert John, Jr.; Beyeler, Walter Eugene; Ames, Arlo Leroy

    2012-02-01

    Complex Adaptive Systems of Systems, or CASoS, are vastly complex physical-socio-technical systems which we must understand to design a secure future for the nation. The Phoenix initiative implements CASoS Engineering principles combining the bottom up Complex Systems and Complex Adaptive Systems view with the top down Systems Engineering and System-of-Systems view. CASoS Engineering theory and practice must be conducted together to develop a discipline that is grounded in reality, extends our understanding of how CASoS behave and allows us to better control the outcomes. The pull of applications (real world problems) is critical to this effort, as is the articulation of a CASoS Engineering Framework that grounds an engineering approach in the theory of complex adaptive systems of systems. Successful application of the CASoS Engineering Framework requires modeling, simulation and analysis (MS and A) capabilities and the cultivation of a CASoS Engineering Community of Practice through knowledge sharing and facilitation. The CASoS Engineering Environment, itself a complex adaptive system of systems, constitutes the two platforms that provide these capabilities.

  14. System identification of the Arabidopsis plant circadian system

    NASA Astrophysics Data System (ADS)

    Foo, Mathias; Somers, David E.; Kim, Pan-Jun

    2015-02-01

    The circadian system generates an endogenous oscillatory rhythm that governs the daily activities of organisms in nature. It offers adaptive advantages to organisms through a coordination of their biological functions with the optimal time of day. In this paper, a model of the circadian system in the plant Arabidopsis (species thaliana) is built by using system identification techniques. Prior knowledge about the physical interactions of the genes and the proteins in the plant circadian system is incorporated in the model building exercise. The model is built by using primarily experimentally-verified direct interactions between the genes and the proteins with the available data on mRNA and protein abundances from the circadian system. Our analysis reveals a great performance of the model in predicting the dynamics of the plant circadian system through the effect of diverse internal and external perturbations (gene knockouts and day-length changes). Furthermore, we found that the circadian oscillatory rhythm is robust and does not vary much with the biochemical parameters except those of a light-sensitive protein P and a transcription factor TOC1. In other words, the circadian rhythmic profile is largely a consequence of the network's architecture rather than its particular parameters. Our work suggests that the current experimental knowledge of the gene-to-protein interactions in the plant Arabidopsis, without considering any additional hypothetical interactions, seems to suffice for system-level modeling of the circadian system of this plant and to present an exemplary platform for the control of network dynamics in complex living organisms.

  15. Social networks as embedded complex adaptive systems.

    PubMed

    Benham-Hutchins, Marge; Clancy, Thomas R

    2010-09-01

    As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 15th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, the authors discuss healthcare social networks as a hierarchy of embedded complex adaptive systems. The authors further examine the use of social network analysis tools as a means to understand complex communication patterns and reduce medical errors.

  16. On the identification of hysteretic systems. Part I: Fitness landscapes and evolutionary identification

    NASA Astrophysics Data System (ADS)

    Worden, K.; Manson, G.

    2012-05-01

    Fairly recent work has shown that evolutionary optimisation schemes (genetic algorithms and differential evolution) offer an effective means of identifying nonlinear dynamical systems, even when the parameter estimation problem is complicated by nonlinearity in the parameters and/or the presence of unmeasured states. In particular, an evolutionary approach to the parameter estimation problem for hysteretic systems has shown promise. The current paper considers aspects of the parameter estimation problem for systems of Bouc-Wen type. In the first place, an investigation into the nature of the objective or cost function for the optimisation is made with the aim of better understanding the performance of the identification scheme. The first part of the paper also discusses the issue of setting initial estimates or ranges for the system parameters. The data on which the analysis is based are generated by computer simulation; the specific evolutionary algorithm considered is Differential Evolution (DE). Although the DE algorithm has proved to be very effective in the identification context, a minor disadvantage manifests itself in the need to set algorithm hyperparameters for the optimisation. This observation leads to the second main objective of the current paper which is to present a recently developed variant of the DE algorithm - the Self-Adaptive Differential Evolution (SADE) algorithm - which learns and adapts a subset of its own hyperparameters throughout the optimisation process. The use of the algorithm for the hysteretic system identification problem is illustrated using the simulated data and it is shown that the algorithm can provide several orders-of-magnitude improvement on the minimisation of the problem objective function.

  17. A hypermedia system for parasite identification.

    PubMed

    Lalle, C

    1996-06-01

    In this paper a hypermedia system for parasite identification is described. The knowledge base is relative to the class of the Trematoda parasites and reports agent, vector, disease, related category of the International Classification of Diseases and geographic area. A graphic user-friendly human-machine interface has been realized for this system.

  18. Adapting classical Systems Engineering to Department of Energy (DOE) needs

    SciTech Connect

    1996-07-01

    Rather than discuss Systems Engineering (SE) as applied by aerospace contractors to military programs, this document provides an adapted model well suited for use by DOE and represents 18 months of applying SE principles to the challenges faced by INEL. The real-life examples are drawn from INEL`s ongoing effort to integrate activities across the entire spectrum of within its Environmental Management program. Since the traditional SE process, with its initial focus on requirements identification and analysis, must be modified to provide tangible results in the short term, the adapted SE model starts with the external driver of ``reducing costs without increasing risks`` and performs an initial integration effort to identify high-potential, cost-saving opportunities. Elements from traditional alternatives development and analysis stages are used; then the adapted model cycles back to include more traditional requirements analysis activities. These cycles continue in an iterative manner, adding rigor and detail at each successive iteration, throughout the life-cycle of a program or project. Detailed lessons learned are included.

  19. Finite-time master-slave synchronization and parameter identification for uncertain Lurie systems.

    PubMed

    Wang, Tianbo; Zhao, Shouwei; Zhou, Wuneng; Yu, Weiqin

    2014-07-01

    This paper investigates the finite-time master-slave synchronization and parameter identification problem for uncertain Lurie systems based on the finite-time stability theory and the adaptive control method. The finite-time master-slave synchronization means that the state of a slave system follows with that of a master system in finite time, which is more reasonable than the asymptotical synchronization in applications. The uncertainties include the unknown parameters and noise disturbances. An adaptive controller and update laws which ensures the synchronization and parameter identification to be realized in finite time are constructed. Finally, two numerical examples are given to show the effectiveness of the proposed method.

  20. System identification by video image processing

    NASA Astrophysics Data System (ADS)

    Shinozuka, Masanobu; Chung, Hung-Chi; Ichitsubo, Makoto; Liang, Jianwen

    2001-07-01

    Emerging image processing techniques demonstrate their potential applications in earthquake engineering, particularly in the area of system identification. In this respect, the objectives of this research are to demonstrate the underlying principle that permits system identification, non-intrusively and remotely, with the aid of video camera and, for the purpose of the proof-of-concept, to apply the principle to a system identification problem involving relative motion, on the basis of the images. In structural control, accelerations at different stories of a building are usually measured and fed back for processing and control. As an alternative, this study attempts to identify the relative motion between different stories of a building for the purpose of on-line structural control by digitizing the images taken by video camera. For this purpose, the video image of the vibration of a structure base-isolated by a friction device under shaking-table was used successfully to observe relative displacement between the isolated structure and the shaking-table. This proof-of-concept experiment demonstrates that the proposed identification method based on digital image processing can be used with appropriate modifications to identify many other engineering-wise significant quantities remotely. In addition to the system identification study in the structural dynamics mentioned above, a result of preliminary study is described involving the video imaging of state of crack damage of road and highway pavement.

  1. Neural Networks and other Techniques for Fault Identification and Isolation of Aircraft Systems

    DTIC Science & Technology

    2003-06-01

    in this paper is based on the use of neural networks (NNs) as on-line learning non-linear approximators. The performances of two different neural...Fault identification, isolation. and accommodation have become critical issues in the overall performance of advanced aircraft systems. Neural ... Networks have shown to be a very attractive alternative to classic adaptation methods for identification and control of non-linear dynamic systems. The

  2. Progress with the lick adaptive optics system

    SciTech Connect

    Gavel, D T; Olivier, S S; Bauman, B; Max, C E; Macintosh, B

    2000-03-01

    Progress and results of observations with the Lick Observatory Laser Guide Star Adaptive Optics System are presented. This system is optimized for diffraction-limited imaging in the near infrared, 1-2 micron wavelength bands. We describe our development efforts in a number of component areas including, a redesign of the optical bench layout, the commissioning of a new infrared science camera, and improvements to the software and user interface. There is also an ongoing effort to characterize the system performance with both natural and laser guide stars and to fold this data into a refined system model. Such a model can be used to help plan future observations, for example, predicting the point-spread function as a function of seeing and guide star magnitude.

  3. Progress with the Lick adaptive optics system

    NASA Astrophysics Data System (ADS)

    Gavel, Donald T.; Olivier, Scot S.; Bauman, Brian J.; Max, Claire E.; Macintosh, Bruce A.

    2000-07-01

    Progress and results of observations with the Lick Observatory Laser Guide Star Adaptive Optics System are presented. This system is optimized for diffraction-limited imaging in the near infrared, 1 - 2 micron wavelength bands. We describe our development efforts in a number of component areas including, a redesign of the optical bench layout, the commissioning of a new infrared science camera, and improvements to the software and user interface. There is also an ongoing effort to characterize the system performance with both natural and laser guide stars and to fold this data into a refined system model. Such a model can be used to help plan future observations, for example, predicting the point-spread function as a function of seeing and guide star magnitude.

  4. The adaptive safety analysis and monitoring system

    NASA Astrophysics Data System (ADS)

    Tu, Haiying; Allanach, Jeffrey; Singh, Satnam; Pattipati, Krishna R.; Willett, Peter

    2004-09-01

    The Adaptive Safety Analysis and Monitoring (ASAM) system is a hybrid model-based software tool for assisting intelligence analysts to identify terrorist threats, to predict possible evolution of the terrorist activities, and to suggest strategies for countering terrorism. The ASAM system provides a distributed processing structure for gathering, sharing, understanding, and using information to assess and predict terrorist network states. In combination with counter-terrorist network models, it can also suggest feasible actions to inhibit potential terrorist threats. In this paper, we will introduce the architecture of the ASAM system, and discuss the hybrid modeling approach embedded in it, viz., Hidden Markov Models (HMMs) to detect and provide soft evidence on the states of terrorist network nodes based on partial and imperfect observations, and Bayesian networks (BNs) to integrate soft evidence from multiple HMMs. The functionality of the ASAM system is illustrated by way of application to the Indian Airlines Hijacking, as modeled from open sources.

  5. Adaptable data management for systems biology investigations

    PubMed Central

    Boyle, John; Rovira, Hector; Cavnor, Chris; Burdick, David; Killcoyne, Sarah; Shmulevich, Ilya

    2009-01-01

    Background Within research each experiment is different, the focus changes and the data is generated from a continually evolving barrage of technologies. There is a continual introduction of new techniques whose usage ranges from in-house protocols through to high-throughput instrumentation. To support these requirements data management systems are needed that can be rapidly built and readily adapted for new usage. Results The adaptable data management system discussed is designed to support the seamless mining and analysis of biological experiment data that is commonly used in systems biology (e.g. ChIP-chip, gene expression, proteomics, imaging, flow cytometry). We use different content graphs to represent different views upon the data. These views are designed for different roles: equipment specific views are used to gather instrumentation information; data processing oriented views are provided to enable the rapid development of analysis applications; and research project specific views are used to organize information for individual research experiments. This management system allows for both the rapid introduction of new types of information and the evolution of the knowledge it represents. Conclusion Data management is an important aspect of any research enterprise. It is the foundation on which most applications are built, and must be easily extended to serve new functionality for new scientific areas. We have found that adopting a three-tier architecture for data management, built around distributed standardized content repositories, allows us to rapidly develop new applications to support a diverse user community. PMID:19265554

  6. An Intelligent Tutoring System Approach to Adaptive Instructional Systems

    DTIC Science & Technology

    2005-09-01

    gr prototypes (scripts) (Schank, 1977). Many software systems have been developed that employ these representations. Many instructional theories and...specific performance or skill-acquisition. However, there are many theories about the number and type of these general abilities. Researchers...Computer Generated Forces and Behavioral Representations. 7.1.2 Role of MAMID in an Adaptive Instructional System Motivation Currently, the student

  7. State Identification in Nonlinear Systems

    SciTech Connect

    Holloway, James Paul

    2005-02-06

    A state estimation method based on finding a system state that causes a model to match a set of system measurements is regularized by requiring that sudden changes in system state be avoided. The required optimization is accomplished by a pattern search algorithm. The method does not require derivative information or linearization of the model. Is has been applied to a 10 dimensional model of a fast reactor system.

  8. A Cross-Cultural Adaptation of the Sniffin' Sticks Olfactory Identification Test for US children.

    PubMed

    Cavazzana, Annachiara; Wesarg, Christiane; Schriever, Valentin A; Hummel, Thomas; Lundström, Johan N; Parma, Valentina

    2017-02-01

    Disorders associated with smell loss are common in adolescents. However, current odor identification tests focus on children from age 6 and older and no cross-cultural test has to date been validated and fully implemented. Here, we aimed to investigate how 3-to-11-year-old US children performed to an adapted and shortened (11 odors instead of 14) version of a European odor identification test-the Sniffin' Kids (Schriever VA, Mori E, Petters W, Boerner C, Smitka M, Hummel T. 2014. The "Sniffin'Kids" test: a 14-item odor identification test for children. Plos One. 9:e101086.). Results confirmed that cued odor identification performance increases with age and revealed little to no differences between girls and boys. Scores below 3 and below 6 may raise hyposmia concerns in US children aged 3-7 years and 8-10 years, respectively. Even though the completion rate of the task reached the 88%, suggesting that children below age 5 were able to finish the test, their performance was relatively poor. In comparing the overall identification performance of US children with that of German children, for whom the test was specifically developed, significant differences emerged, with higher scores obtained by the German sample. Analysis of errors indicated that a lack of semantic knowledge for the olfactory-presented objects may be at the root of poor identification skills in US children and therefore constitutes a problem in the development of an odor identification test for younger children valid across cultures.

  9. Adaptive system for eye-fundus imaging

    SciTech Connect

    Larichev, A V; Ivanov, P V; Iroshnikov, N G; Shmalgauzen, V I; Otten, L J

    2002-10-31

    A compact adaptive system capable of imaging a human-eye retina with a spatial resolution as high as 6 {mu}m and a field of view of 15{sup 0} is developed. It is shown that a modal bimorph corrector with nonlocalised response functions provides the efficient suppression of dynamic aberrations of a human eye. The residual root-mean-square error in correction of aberrations of a real eye with nonparalysed accommodation lies in the range of 0.1 - 0.15 {mu}m.

  10. NASA Facts: Nanosatellite Launch Adapter System (NLAS)

    NASA Technical Reports Server (NTRS)

    Chartres, James; Cappuccio, Gelsomina

    2013-01-01

    The Nanosatellite Launch Adapter System (NLAS) was developed to increase access to space while simplifying the integration process of miniature satellites, called nanosats or cubesats, onto launch vehicles. A standard cubesat measures about 4inches (10 cm) long, 4 inches wide,and 4 inches high, and is called a one-unit (1U) cubesat. A single NLAS provides the capability to deploy 24U of cubesats. The system is designed to accommodate satellites measuring 1U, 1.5U, 2U, 3U and 6U sizes for deployment into orbit. The NLAS may be configured for use on different launch vehicles. The system also enables flight demonstrations of new technologies in the space environment.

  11. System Identification and Simulation of a Triaxial Shaker System,

    DTIC Science & Technology

    1996-01-01

    methods. Results of the system identification process are discussed. Certain methods are found to produce models that are in good agreement with measured response data from the actual shaker system....implemented in the simulation. The first is a physically-based model derived from a finite element analysis together with a model-updating system ... identification scheme; the second is a parametric model without direct physical significance. The advantages and disadvantages of each model for this

  12. Continuous-Time Bilinear System Identification

    NASA Technical Reports Server (NTRS)

    Juang, Jer-Nan

    2003-01-01

    The objective of this paper is to describe a new method for identification of a continuous-time multi-input and multi-output bilinear system. The approach is to make judicious use of the linear-model properties of the bilinear system when subjected to a constant input. Two steps are required in the identification process. The first step is to use a set of pulse responses resulting from a constant input of one sample period to identify the state matrix, the output matrix, and the direct transmission matrix. The second step is to use another set of pulse responses with the same constant input over multiple sample periods to identify the input matrix and the coefficient matrices associated with the coupling terms between the state and the inputs. Numerical examples are given to illustrate the concept and the computational algorithm for the identification method.

  13. Application of System Identification in Engineering

    NASA Astrophysics Data System (ADS)

    Natke, H. G.

    System identification is a powerful tool in engineering. Its various methods in the frequency and in the time domain have been extensively discussed in earlier CISM courses. The aim of this course is to describe the state of the art in specific application areas, such as estimation of eigenquantities (in the aerospace industry, in civil engineering, in naval engineering etc.), noise source detection, fault detection by investigation of dynamic properties, such as machine sound characteristics, and the identification of the dynamic behaviour of flow induced systems (e.g. aerolastic problems). Geotechnical applications are also among the fields of interest. The lecture notes contain demonstrations of several methods and include a valuation by combining various kinds of experience. Such complex information includes not only theoretical aspects of identification but also advice on practical handling, for example concerning testing effort and data handling.

  14. Robust identification of local adaptation from allele frequencies.

    PubMed

    Günther, Torsten; Coop, Graham

    2013-09-01

    Comparing allele frequencies among populations that differ in environment has long been a tool for detecting loci involved in local adaptation. However, such analyses are complicated by an imperfect knowledge of population allele frequencies and neutral correlations of allele frequencies among populations due to shared population history and gene flow. Here we develop a set of methods to robustly test for unusual allele frequency patterns and correlations between environmental variables and allele frequencies while accounting for these complications based on a Bayesian model previously implemented in the software Bayenv. Using this model, we calculate a set of "standardized allele frequencies" that allows investigators to apply tests of their choice to multiple populations while accounting for sampling and covariance due to population history. We illustrate this first by showing that these standardized frequencies can be used to detect nonparametric correlations with environmental variables; these correlations are also less prone to spurious results due to outlier populations. We then demonstrate how these standardized allele frequencies can be used to construct a test to detect SNPs that deviate strongly from neutral population structure. This test is conceptually related to FST and is shown to be more powerful, as we account for population history. We also extend the model to next-generation sequencing of population pools-a cost-efficient way to estimate population allele frequencies, but one that introduces an additional level of sampling noise. The utility of these methods is demonstrated in simulations and by reanalyzing human SNP data from the Human Genome Diversity Panel populations and pooled next-generation sequencing data from Atlantic herring. An implementation of our method is available from http://gcbias.org.

  15. 75 FR 49869 - Changes to Standard Numbering System, Vessel Identification System, and Boating Accident Report...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-08-16

    ..., Vessel Identification System, and Boating Accident Report Database AGENCY: Coast Guard, DHS. ACTION..., Vessel Identification System, and Boating Accident Report Database. DATES: Comments and related material...) proposing changes in the Standard Numbering System, Vessel Identification System, and Boating...

  16. Adaptive Decision Aiding in Computer-Assisted Instruction: Adaptive Computerized Training System (ACTS).

    ERIC Educational Resources Information Center

    Hopf-Weichel, Rosemarie; And Others

    This report describes results of the first year of a three-year program to develop and evaluate a new Adaptive Computerized Training System (ACTS) for electronics maintenance training. (ACTS incorporates an adaptive computer program that learns the student's diagnostic and decision value structure, compares it to that of an expert, and adapts the…

  17. The Adaptive Immune System of Haloferax volcanii.

    PubMed

    Maier, Lisa-Katharina; Dyall-Smith, Mike; Marchfelder, Anita

    2015-02-16

    To fight off invading genetic elements, prokaryotes have developed an elaborate defence system that is both adaptable and heritable-the CRISPR-Cas system (CRISPR is short for: clustered regularly interspaced short palindromic repeats and Cas: CRISPR associated). Comprised of proteins and multiple small RNAs, this prokaryotic defence system is present in 90% of archaeal and 40% of bacterial species, and enables foreign intruders to be eliminated in a sequence-specific manner. There are three major types (I-III) and at least 14 subtypes of this system, with only some of the subtypes having been analysed in detail, and many aspects of the defence reaction remaining to be elucidated. Few archaeal examples have so far been analysed. Here we summarize the characteristics of the CRISPR-Cas system of Haloferax volcanii, an extremely halophilic archaeon originally isolated from the Dead Sea. It carries a single CRISPR-Cas system of type I-B, with a Cascade like complex composed of Cas proteins Cas5, Cas6b and Cas7. Cas6b is essential for CRISPR RNA (crRNA) maturation but is otherwise not required for the defence reaction. A systematic search revealed that six protospacer adjacent motif (PAM) sequences are recognised by the Haloferax defence system. For successful invader recognition, a non-contiguous seed sequence of 10 base-pairs between the crRNA and the invader is required.

  18. Parametric uncertain identification of a robotic system

    NASA Astrophysics Data System (ADS)

    Angel, L.; Viola, J.; Hernández, C.

    2016-07-01

    This paper presents the parametric uncertainties identification of a robotic system of one degree of freedom. A MSC-ADAMS / MATLAB co-simulation model was built to simulate the uncertainties that affect the robotic system. For a desired trajectory, a set of dynamic models of the system was identified in presence of variations in the mass, length and friction of the system employing least squares method. Using the input-output linearization technique a linearized model plant was defined. Finally, the maximum multiplicative uncertainty of the system was modelled giving the controller desired design conditions to achieve a robust stability and performance of the closed loop system.

  19. Adaptable formations utilizing heterogeneous unmanned systems

    NASA Astrophysics Data System (ADS)

    Barnes, Laura E.; Garcia, Richard; Fields, MaryAnne; Valavanis, Kimon

    2009-05-01

    This paper addresses the problem of controlling and coordinating heterogeneous unmanned systems required to move as a group while maintaining formation. We propose a strategy to coordinate groups of unmanned ground vehicles (UGVs) with one or more unmanned aerial vehicles (UAVs). UAVs can be utilized in one of two ways: (1) as alpha robots to guide the UGVs; and (2) as beta robots to surround the UGVs and adapt accordingly. In the first approach, the UAV guides a swarm of UGVs controlling their overall formation. In the second approach, the UGVs guide the UAVs controlling their formation. The unmanned systems are brought into a formation utilizing artificial potential fields generated from normal and sigmoid functions. These functions control the overall swarm geometry. Nonlinear limiting functions are defined to provide tighter swarm control by modifying and adjusting a set of control variables forcing the swarm to behave according to set constraints. Formations derived are subsets of elliptical curves but can be generalized to any curvilinear shape. Both approaches are demonstrated in simulation and experimentally. To demonstrate the second approach in simulation, a swarm of forty UAVs is utilized in a convoy protection mission. As a convoy of UGVs travels, UAVs dynamically and intelligently adapt their formation in order to protect the convoy of vehicles as it moves. Experimental results are presented to demonstrate the approach using a fully autonomous group of three UGVs and a single UAV helicopter for coordination.

  20. Adaptive cyber-attack modeling system

    NASA Astrophysics Data System (ADS)

    Gonsalves, Paul G.; Dougherty, Edward T.

    2006-05-01

    The pervasiveness of software and networked information systems is evident across a broad spectrum of business and government sectors. Such reliance provides an ample opportunity not only for the nefarious exploits of lone wolf computer hackers, but for more systematic software attacks from organized entities. Much effort and focus has been placed on preventing and ameliorating network and OS attacks, a concomitant emphasis is required to address protection of mission critical software. Typical software protection technique and methodology evaluation and verification and validation (V&V) involves the use of a team of subject matter experts (SMEs) to mimic potential attackers or hackers. This manpower intensive, time-consuming, and potentially cost-prohibitive approach is not amenable to performing the necessary multiple non-subjective analyses required to support quantifying software protection levels. To facilitate the evaluation and V&V of software protection solutions, we have designed and developed a prototype adaptive cyber attack modeling system. Our approach integrates an off-line mechanism for rapid construction of Bayesian belief network (BN) attack models with an on-line model instantiation, adaptation and knowledge acquisition scheme. Off-line model construction is supported via a knowledge elicitation approach for identifying key domain requirements and a process for translating these requirements into a library of BN-based cyber-attack models. On-line attack modeling and knowledge acquisition is supported via BN evidence propagation and model parameter learning.

  1. Optical disk uses in criminal identification systems

    NASA Astrophysics Data System (ADS)

    Sypherd, Allen D.

    1990-08-01

    A significant advancement in law enforcement tools has been made possible by the rapid and innovative development of electronic imaging for criminal identification systems. In particular, development of optical disks capable of high-capacity and random-access storage has provided a unique marriage of application and technology. Fast random access to any record, non-destructive reading of stored images, electronic sorting and transmission of images and an accepted legal basis for evidence are a few of the advantages derived from optical disk technology. This paper discusses the application of optical disk technology to both Automated Fingerprint Identification Systems (AFIS) and Automated Mugshot Retrieval Systems (AMRS). The following topics are addressed in light of AFIS and AMRS user requirements and system capabilities: Write once vs. rewritable, gray level and storage requirements, multi-volume library systems, data organization and capacity trends.

  2. Rotorcraft System Identification (Identification des Systemes de Voilures Tournantes)

    DTIC Science & Technology

    1991-10-01

    139, 1985. DuVal, R.W., Wang , .C. and Demiroz, M.Y.: A Practtcal Approach to Rotorcraft Systems Padfield, G.D., Thorne, R., Murray-Smith, D...an experimentel verification of the Kalman filter iRA)YOUG, PETER, (AB)PATTOn, ROALD J implementation, sod an experimental evaluation of filter...The estimation of the measurements wlth the RSRA compound helicopter parameter values in this model (the stability and control derivatives) (AA) WANG

  3. 78 FR 58785 - Unique Device Identification System

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-09-24

    ... September 24, 2013 Part V Department of Health and Human Service Food and Drug Administration 21 CFR Parts... SERVICES Food and Drug Administration 21 CFR Parts 16, 801, 803, 806, 810, 814, 820, 821, 822, and 830 RIN 0910-AG31 Unique Device Identification System AGENCY: Food and Drug Administration, HHS. ACTION:...

  4. Improved system identification with Renormalization Group.

    PubMed

    Wang, Qing-Guo; Yu, Chao; Zhang, Yong

    2014-09-01

    This paper proposes an improved system identification method with Renormalization Group. Renormalization Group is applied to a fine data set to obtain a coarse data set. The least squares algorithm is performed on the coarse data set. The theoretical analysis under certain conditions shows that the parameter estimation error could be reduced. The proposed method is illustrated with examples.

  5. 49 CFR 1542.211 - Identification systems.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 49 Transportation 9 2014-10-01 2014-10-01 false Identification systems. 1542.211 Section 1542.211 Transportation Other Regulations Relating to Transportation (Continued) TRANSPORTATION SECURITY ADMINISTRATION, DEPARTMENT OF HOMELAND SECURITY CIVIL AVIATION SECURITY AIRPORT SECURITY Operations § 1542.211...

  6. 49 CFR 1542.211 - Identification systems.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 49 Transportation 9 2012-10-01 2012-10-01 false Identification systems. 1542.211 Section 1542.211 Transportation Other Regulations Relating to Transportation (Continued) TRANSPORTATION SECURITY ADMINISTRATION, DEPARTMENT OF HOMELAND SECURITY CIVIL AVIATION SECURITY AIRPORT SECURITY Operations § 1542.211...

  7. 49 CFR 1542.211 - Identification systems.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 49 Transportation 9 2010-10-01 2010-10-01 false Identification systems. 1542.211 Section 1542.211 Transportation Other Regulations Relating to Transportation (Continued) TRANSPORTATION SECURITY ADMINISTRATION, DEPARTMENT OF HOMELAND SECURITY CIVIL AVIATION SECURITY AIRPORT SECURITY Operations § 1542.211...

  8. 49 CFR 1542.211 - Identification systems.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 49 Transportation 9 2013-10-01 2013-10-01 false Identification systems. 1542.211 Section 1542.211 Transportation Other Regulations Relating to Transportation (Continued) TRANSPORTATION SECURITY ADMINISTRATION, DEPARTMENT OF HOMELAND SECURITY CIVIL AVIATION SECURITY AIRPORT SECURITY Operations § 1542.211...

  9. 49 CFR 1542.211 - Identification systems.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 49 Transportation 9 2011-10-01 2011-10-01 false Identification systems. 1542.211 Section 1542.211 Transportation Other Regulations Relating to Transportation (Continued) TRANSPORTATION SECURITY ADMINISTRATION, DEPARTMENT OF HOMELAND SECURITY CIVIL AVIATION SECURITY AIRPORT SECURITY Operations § 1542.211...

  10. Serial identification of EEG patterns using adaptive wavelet-based analysis

    NASA Astrophysics Data System (ADS)

    Nazimov, A. I.; Pavlov, A. N.; Nazimova, A. A.; Grubov, V. V.; Koronovskii, A. A.; Sitnikova, E.; Hramov, A. E.

    2013-10-01

    A problem of recognition specific oscillatory patterns in the electroencephalograms with the continuous wavelet-transform is discussed. Aiming to improve abilities of the wavelet-based tools we propose a serial adaptive method for sequential identification of EEG patterns such as sleep spindles and spike-wave discharges. This method provides an optimal selection of parameters based on objective functions and enables to extract the most informative features of the recognized structures. Different ways of increasing the quality of patterns recognition within the proposed serial adaptive technique are considered.

  11. Adaptive automatic balancing of magnetic bearing systems

    NASA Astrophysics Data System (ADS)

    Kim, Jong-Sun

    Rotating machinery including magnetic bearings are usually persistently excited by the rotation related disturbances such as mass unbalance; hence there exists a residual vibration in the steady state response even if the closed loop system is asymptotically stable. In order to control the periodic disturbances, a disturbance accommodating controller (DAC) is designed based on the disturbance estimator and applied to the forced balancing of magnetic bearing system. The control objective is to minimize the synchronous component of shaft displacement or control current. In order to account for the variation of the disturbance model due to the shaft of operating speed, an adaptive disturbance accommodating control scheme is developed based on a certain optimality criterion. The continuous time design discretized to implement the controller in the digital computer and the merits and demerits are studied numerically. It is shown that the proposed method is efficient in reducing rotor unbalance and automatic balancing.

  12. Contrarian behavior in a complex adaptive system

    NASA Astrophysics Data System (ADS)

    Liang, Y.; An, K. N.; Yang, G.; Huang, J. P.

    2013-01-01

    Contrarian behavior is a kind of self-organization in complex adaptive systems (CASs). Here we report the existence of a transition point in a model resource-allocation CAS with contrarian behavior by using human experiments, computer simulations, and theoretical analysis. The resource ratio and system predictability serve as the tuning parameter and order parameter, respectively. The transition point helps to reveal the positive or negative role of contrarian behavior. This finding is in contrast to the common belief that contrarian behavior always has a positive role in resource allocation, say, stabilizing resource allocation by shrinking the redundancy or the lack of resources. It is further shown that resource allocation can be optimized at the transition point by adding an appropriate size of contrarians. This work is also expected to be of value to some other fields ranging from management and social science to ecology and evolution.

  13. Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS)

    NASA Technical Reports Server (NTRS)

    Masek, Jeffrey G.

    2006-01-01

    The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) project is creating a record of forest disturbance and regrowth for North America from the Landsat satellite record, in support of the carbon modeling activities. LEDAPS relies on the decadal Landsat GeoCover data set supplemented by dense image time series for selected locations. Imagery is first atmospherically corrected to surface reflectance, and then change detection algorithms are used to extract disturbance area, type, and frequency. Reuse of the MODIS Land processing system (MODAPS) architecture allows rapid throughput of over 2200 MSS, TM, and ETM+ scenes. Initial ("Beta") surface reflectance products are currently available for testing, and initial continental disturbance products will be available by the middle of 2006.

  14. Contrarian behavior in a complex adaptive system.

    PubMed

    Liang, Y; An, K N; Yang, G; Huang, J P

    2013-01-01

    Contrarian behavior is a kind of self-organization in complex adaptive systems (CASs). Here we report the existence of a transition point in a model resource-allocation CAS with contrarian behavior by using human experiments, computer simulations, and theoretical analysis. The resource ratio and system predictability serve as the tuning parameter and order parameter, respectively. The transition point helps to reveal the positive or negative role of contrarian behavior. This finding is in contrast to the common belief that contrarian behavior always has a positive role in resource allocation, say, stabilizing resource allocation by shrinking the redundancy or the lack of resources. It is further shown that resource allocation can be optimized at the transition point by adding an appropriate size of contrarians. This work is also expected to be of value to some other fields ranging from management and social science to ecology and evolution.

  15. Identification of Metabolic Pathway Systems

    PubMed Central

    Dolatshahi, Sepideh; Voit, Eberhard O.

    2016-01-01

    The estimation of parameters in even moderately large biological systems is a significant challenge. This challenge is greatly exacerbated if the mathematical formats of appropriate process descriptions are unknown. To address this challenge, the method of dynamic flux estimation (DFE) was proposed for the analysis of metabolic time series data. Under ideal conditions, the first phase of DFE yields numerical representations of all fluxes within a metabolic pathway system, either as values at each time point or as plots against their substrates and modulators. However, this numerical result does not reveal the mathematical format of each flux. Thus, the second phase of DFE selects functional formats that are consistent with the numerical trends obtained from the first phase. While greatly facilitating metabolic data analysis, DFE is only directly applicable if the pathway system contains as many dependent variables as fluxes. Because most actual systems contain more fluxes than metabolite pools, this requirement is seldom satisfied. Auxiliary methods have been proposed to alleviate this issue, but they are not general. Here we propose strategies that extend DFE toward general, slightly underdetermined pathway systems. PMID:26904095

  16. An efficient automatic firearm identification system

    NASA Astrophysics Data System (ADS)

    Chuan, Zun Liang; Liong, Choong-Yeun; Jemain, Abdul Aziz; Ghani, Nor Azura Md.

    2014-06-01

    Automatic firearm identification system (AFIS) is highly demanded in forensic ballistics to replace the traditional approach which uses comparison microscope and is relatively complex and time consuming. Thus, several AFIS have been developed for commercial and testing purposes. However, those AFIS are still unable to overcome some of the drawbacks of the traditional firearm identification approach. The goal of this study is to introduce another efficient and effective AFIS. A total of 747 firing pin impression images captured from five different pistols of same make and model are used to evaluate the proposed AFIS. It was demonstrated that the proposed AFIS is capable of producing firearm identification accuracy rate of over 95.0% with an execution time of less than 0.35 seconds per image.

  17. Nonlinear identification of MDOF systems using Volterra series approximation

    NASA Astrophysics Data System (ADS)

    Prawin, J.; Rao, A. Rama Mohan

    2017-02-01

    Most of the practical engineering structures exhibit nonlinearity due to nonlinear dynamic characteristics of structural joints, nonlinear boundary conditions and nonlinear material properties. Meanwhile, the presence of non-linearity in the system can lead to a wide range of structural behavior, for example, jumps, limit cycles, internal resonances, modal coupling, super and sub-harmonic resonances, etc. In this paper, we present a Volterra series approximation approach based on the adaptive filter concept for nonlinear identification of multi-degree of freedom systems, without sacrificing the benefits associated with the traditional Volterra series approach. The effectiveness of the proposed approach is demonstrated using two classical single degrees of freedom systems (breathing crack problem and Duffing Holmes oscillator) and later we extend to multi-degree of freedom systems.

  18. Flipping Adapters for Space Launch System

    NASA Video Gallery

    The structural test article adapter is flipped at Marshall testing facility Building 4705. The turnover is an important step in finishing the machining work on the adapter, which will undergo tests...

  19. The Limits to Adaptation: A Systems Approach

    EPA Science Inventory

    The ability to adapt to climate change is delineated by capacity thresholds, after which climate damages begin to overwhelm the adaptation response. Such thresholds depend upon physical properties (natural processes and engineering parameters), resource constraints (expressed th...

  20. 33 CFR 401.20 - Automatic Identification System.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ...' maritime Differential Global Positioning System radiobeacon services; or (7) The use of a temporary unit... 33 Navigation and Navigable Waters 3 2013-07-01 2013-07-01 false Automatic Identification System... Identification System. (a) Each of the following vessels must use an Automatic Identification System...

  1. 33 CFR 401.20 - Automatic Identification System.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ...' maritime Differential Global Positioning System radiobeacon services; or (7) The use of a temporary unit... 33 Navigation and Navigable Waters 3 2012-07-01 2012-07-01 false Automatic Identification System... Identification System. (a) Each of the following vessels must use an Automatic Identification System...

  2. 33 CFR 401.20 - Automatic Identification System.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ...' maritime Differential Global Positioning System radiobeacon services; or (7) The use of a temporary unit... 33 Navigation and Navigable Waters 3 2011-07-01 2011-07-01 false Automatic Identification System... Identification System. (a) Each of the following vessels must use an Automatic Identification System...

  3. 33 CFR 401.20 - Automatic Identification System.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ...' maritime Differential Global Positioning System radiobeacon services; or (7) The use of a temporary unit... 33 Navigation and Navigable Waters 3 2014-07-01 2014-07-01 false Automatic Identification System... Identification System. (a) Each of the following vessels must use an Automatic Identification System...

  4. 33 CFR 401.20 - Automatic Identification System.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ...' maritime Differential Global Positioning System radiobeacon services; or (7) The use of a temporary unit... 33 Navigation and Navigable Waters 3 2010-07-01 2010-07-01 false Automatic Identification System... Identification System. (a) Each of the following vessels must use an Automatic Identification System...

  5. An Investigation of System Identification Techniques for Simulation Model Abstraction

    DTIC Science & Technology

    2000-02-01

    This report summarizes research into the application of system identification techniques to simulation model abstraction. System identification produces...34Mission Simulation," a simulation of a squadron of aircraft performing battlefield air interdiction. The system identification techniques were...simplified mathematical models that approximate the dynamic behaviors of the underlying stochastic simulations. Four state-space system

  6. Intercellular Communication in the Adaptive Immune System

    NASA Astrophysics Data System (ADS)

    Chakraborty, Arup

    2004-03-01

    Higher organisms, like humans, have an adaptive immune system that can respond to pathogens that have not been encountered before. T lymphocytes (T cells) are the orchestrators of the adaptive immune response. They interact with cells, called antigen presenting cells (APC), that display molecular signatures of pathogens. Recently, video microscopy experiments have revealed that when T cells detect antigen on APC surfaces, a spatially patterned supramolecular assembly of different types of molecules forms in the junction between cell membranes. This recognition motif is implicated in information transfer between APC and T cells, and so, is labeled the immunological synapse. The observation of synapse formation sparked two broad questions: How does the synapse form? Why does the synapse form? I will describe progress made in answering these fundamental questions in biology by synergistic use of statistical mechanical theory/computation, chemical engineering principles, and genetic and biochemical experiments. The talk will also touch upon mechanisms that may underlie the extreme sensitivity with which T cells discriminate between self and non-self.

  7. Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems

    NASA Astrophysics Data System (ADS)

    Volyanskyy, Kostyantyn Y.

    Neural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we develop a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture with additional terms in the update laws that are constructed using a moving window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress system uncertainty. Linear and nonlinear parameterizations of the system uncertainty are considered and state and output feedback neuroadaptive controllers are developed. Furthermore, we extend the developed framework to discrete-time dynamical systems. To illustrate the efficacy of the proposed approach we apply our results to an aircraft model with wing rock dynamics, a spacecraft model with unknown moment of inertia, and an unmanned combat aerial vehicle undergoing actuator failures, and compare our results with standard neuroadaptive control methods. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A sub-class of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this dissertation, we develop direct adaptive and neuroadaptive control framework for stabilization, disturbance

  8. Rapid identification of Candida dubliniensis with commercial yeast identification systems.

    PubMed

    Pincus, D H; Coleman, D C; Pruitt, W R; Padhye, A A; Salkin, I F; Geimer, M; Bassel, A; Sullivan, D J; Clarke, M; Hearn, V

    1999-11-01

    Candida dubliniensis is a newly described species that is closely related phylogenetically to Candida albicans and that is commonly associated with oral candidiasis in human immunodeficiency virus-positive patients. Several recent studies have attempted to elucidate phenotypic and genotypic characteristics of use in separating the two species. However, results obtained with simple phenotypic tests were too variable and tests that provided more definitive data were too complex for routine use in the clinical laboratory setting. The objective of this study was to determine if reproducible identification of C. dubliniensis could be obtained with commercial identification kits. The substrate reactivity profiles of 80 C. dubliniensis isolates were obtained by using the API 20C AUX, ID 32 C, RapID Yeast Plus, VITEK YBC, and VITEK 2 ID-YST systems. The percentages of C. dubliniensis isolates capable of assimilating or hydrolyzing each substrate were compared with the percentages from the C. albicans profiles in each kit's database, and the results were expressed as percent C. dubliniensis and percent C. albicans. Any substrate that showed >50% difference in reactivity was considered useful in differentiating the species. In addition, assimilation of methyl-alpha-D-glucoside (MDG), D-trehalose (TRE), and D-xylose (XYL) by the same isolates was investigated by the traditional procedure of Wickerham and Burton (L. J. Wickerham and K. A. Burton, J. Bacteriol. 56:363-371, 1948). At 48 h (the time recommended by the manufacturer for its new database), we found that the assimilation of four carbohydrates in the API 20C AUX system could be used to distinguish the species, i.e., glycerol (GLY; 88 and 14%), XYL (0 and 88%), MDG (0 and 85%), and TRE (15 and 97%). Similarly, results with the ID 32 C system at 48 h showed that XYL (0 and 98%), MDG (0 and 98%), lactate (LAT; 0 and 96%), and TRE (30 and 96%) could be used to separate the two species. Phosphatase (PHS; 9 and 76%) and

  9. Simulation of DKIST solar adaptive optics system

    NASA Astrophysics Data System (ADS)

    Marino, Jose; Carlisle, Elizabeth; Schmidt, Dirk

    2016-07-01

    Solar adaptive optics (AO) simulations are a valuable tool to guide the design and optimization process of current and future solar AO and multi-conjugate AO (MCAO) systems. Solar AO and MCAO systems rely on extended object cross-correlating Shack-Hartmann wavefront sensors to measure the wavefront. Accurate solar AO simulations require computationally intensive operations, which have until recently presented a prohibitive computational cost. We present an update on the status of a solar AO and MCAO simulation tool being developed at the National Solar Observatory. The simulation tool is a multi-threaded application written in the C++ language that takes advantage of current large multi-core CPU computer systems and fast ethernet connections to provide accurate full simulation of solar AO and MCAO systems. It interfaces with KAOS, a state of the art solar AO control software developed by the Kiepenheuer-Institut fuer Sonnenphysik, that provides reliable AO control. We report on the latest results produced by the solar AO simulation tool.

  10. Herd behavior in a complex adaptive system

    PubMed Central

    Zhao, Li; Yang, Guang; Wang, Wei; Chen, Yu; Huang, J. P.; Ohashi, Hirotada; Stanley, H. Eugene

    2011-01-01

    In order to survive, self-serving agents in various kinds of complex adaptive systems (CASs) must compete against others for sharing limited resources with biased or unbiased distribution by conducting strategic behaviors. This competition can globally result in the balance of resource allocation. As a result, most of the agents and species can survive well. However, it is a common belief that the formation of a herd in a CAS will cause excess volatility, which can ruin the balance of resource allocation in the CAS. Here this belief is challenged with the results obtained from a modeled resource-allocation system. Based on this system, we designed and conducted a series of computer-aided human experiments including herd behavior. We also performed agent-based simulations and theoretical analyses, in order to confirm the experimental observations and reveal the underlying mechanism. We report that, as long as the ratio of the two resources for allocation is biased enough, the formation of a typically sized herd can help the system to reach the balanced state. This resource ratio also serves as the critical point for a class of phase transition identified herein, which can be used to discover the role change of herd behavior, from a ruinous one to a helpful one. This work is also of value to some fields, ranging from management and social science, to ecology and evolution, and to physics. PMID:21876133

  11. Herd behavior in a complex adaptive system.

    PubMed

    Zhao, Li; Yang, Guang; Wang, Wei; Chen, Yu; Huang, J P; Ohashi, Hirotada; Stanley, H Eugene

    2011-09-13

    In order to survive, self-serving agents in various kinds of complex adaptive systems (CASs) must compete against others for sharing limited resources with biased or unbiased distribution by conducting strategic behaviors. This competition can globally result in the balance of resource allocation. As a result, most of the agents and species can survive well. However, it is a common belief that the formation of a herd in a CAS will cause excess volatility, which can ruin the balance of resource allocation in the CAS. Here this belief is challenged with the results obtained from a modeled resource-allocation system. Based on this system, we designed and conducted a series of computer-aided human experiments including herd behavior. We also performed agent-based simulations and theoretical analyses, in order to confirm the experimental observations and reveal the underlying mechanism. We report that, as long as the ratio of the two resources for allocation is biased enough, the formation of a typically sized herd can help the system to reach the balanced state. This resource ratio also serves as the critical point for a class of phase transition identified herein, which can be used to discover the role change of herd behavior, from a ruinous one to a helpful one. This work is also of value to some fields, ranging from management and social science, to ecology and evolution, and to physics.

  12. Structural system identification: Structural dynamics model validation

    SciTech Connect

    Red-Horse, J.R.

    1997-04-01

    Structural system identification is concerned with the development of systematic procedures and tools for developing predictive analytical models based on a physical structure`s dynamic response characteristics. It is a multidisciplinary process that involves the ability (1) to define high fidelity physics-based analysis models, (2) to acquire accurate test-derived information for physical specimens using diagnostic experiments, (3) to validate the numerical simulation model by reconciling differences that inevitably exist between the analysis model and the experimental data, and (4) to quantify uncertainties in the final system models and subsequent numerical simulations. The goal of this project was to develop structural system identification techniques and software suitable for both research and production applications in code and model validation.

  13. Parameter identification for nonlinear aerodynamic systems

    NASA Technical Reports Server (NTRS)

    Pearson, Allan E.

    1990-01-01

    Parameter identification for nonlinear aerodynamic systems is examined. It is presumed that the underlying model can be arranged into an input/output (I/O) differential operator equation of a generic form. The algorithm estimation is especially efficient since the equation error can be integrated exactly given any I/O pair to obtain an algebraic function of the parameters. The algorithm for parameter identification was extended to the order determination problem for linear differential system. The degeneracy in a least squares estimate caused by feedback was addressed. A method of frequency analysis for determining the transfer function G(j omega) from transient I/O data was formulated using complex valued Fourier based modulating functions in contrast with the trigonometric modulating functions for the parameter estimation problem. A simulation result of applying the algorithm is given under noise-free conditions for a system with a low pass transfer function.

  14. Adaptive model training system and method

    DOEpatents

    Bickford, Randall L; Palnitkar, Rahul M; Lee, Vo

    2014-04-15

    An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.

  15. Adaptive model training system and method

    DOEpatents

    Bickford, Randall L; Palnitkar, Rahul M

    2014-11-18

    An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.

  16. Intelligent Optical Systems Using Adaptive Optics

    NASA Technical Reports Server (NTRS)

    Clark, Natalie

    2012-01-01

    Until recently, the phrase adaptive optics generally conjured images of large deformable mirrors being integrated into telescopes to compensate for atmospheric turbulence. However, the development of smaller, cheaper devices has sparked interest for other aerospace and commercial applications. Variable focal length lenses, liquid crystal spatial light modulators, tunable filters, phase compensators, polarization compensation, and deformable mirrors are becoming increasingly useful for other imaging applications including guidance navigation and control (GNC), coronagraphs, foveated imaging, situational awareness, autonomous rendezvous and docking, non-mechanical zoom, phase diversity, and enhanced multi-spectral imaging. The active components presented here allow flexibility in the optical design, increasing performance. In addition, the intelligent optical systems presented offer advantages in size and weight and radiation tolerance.

  17. Simulating Astronomical Adaptive Optics Systems Using Yao

    NASA Astrophysics Data System (ADS)

    Rigaut, François; Van Dam, Marcos

    2013-12-01

    Adaptive Optics systems are at the heart of the coming Extremely Large Telescopes generation. Given the importance, complexity and required advances of these systems, being able to simulate them faithfully is key to their success, and thus to the success of the ELTs. The type of systems envisioned to be built for the ELTs cover most of the AO breeds, from NGS AO to multiple guide star Ground Layer, Laser Tomography and Multi-Conjugate AO systems, with typically a few thousand actuators. This represents a large step up from the current generation of AO systems, and accordingly a challenge for existing AO simulation packages. This is especially true as, in the past years, computer power has not been following Moore's law in its most common understanding; CPU clocks are hovering at about 3GHz. Although the use of super computers is a possible solution to run these simulations, being able to use smaller machines has obvious advantages: cost, access, environmental issues. By using optimised code in an already proven AO simulation platform, we were able to run complex ELT AO simulations on very modest machines, including laptops. The platform is YAO. In this paper, we describe YAO, its architecture, its capabilities, the ELT-specific challenges and optimisations, and finally its performance. As an example, execution speed ranges from 5 iterations per second for a 6 LGS 60x60 subapertures Shack-Hartmann Wavefront sensor Laser Tomography AO system (including full physical image formation and detector characteristics) up to over 30 iterations/s for a single NGS AO system.

  18. Digital Control and Identification of Distributed Systems.

    DTIC Science & Technology

    1990-08-14

    for example, problems in which a Schrodinger equation is coupled with a diffusion equation . In this paper, we are particularly interested in second...control of systems represented by partial differential equations , and adaptive control and tracking problems for flexible structures and manipulators...and functional differential equations . The primary class of applications is large flexible space structures. Papers dealing mainly with approximation

  19. Model Identification and Validation for a Heating System using MATLAB System Identification Toolbox

    NASA Astrophysics Data System (ADS)

    Junaid Rabbani, Muhammad; Hussain, Kashan; khan, Asim-ur-Rehman; Ali, Abdullah

    2013-12-01

    This paper proposed a systematic approach to select a mathematical model for an industrial heating system by adopting system identification techniques with the aim of fulfilling the design requirement for the controller. The model identification process will begin by collecting real measurement data samples with the aid of MATLAB system identification toolbox. The criteria for selecting the model that could validate model output with actual data will based upon: parametric identification technique, picking the best model structure with low order among ARX, ARMAX and BJ, and then applying model estimation and validation tests. Simulated results have shown that the BJ model has been best in providing good estimation and validation based upon performance criteria such as: final prediction error, loss function, best percentage of model fit, and co-relation analysis of residual for output.

  20. A Gamma Memory Neural Network for System Identification

    NASA Technical Reports Server (NTRS)

    Motter, Mark A.; Principe, Jose C.

    1992-01-01

    A gamma neural network topology is investigated for a system identification application. A discrete gamma memory structure is used in the input layer, providing delayed values of both the control inputs and the network output to the input layer. The discrete gamma memory structure implements a tapped dispersive delay line, with the amount of dispersion regulated by a single, adaptable parameter. The network is trained using static back propagation, but captures significant features of the system dynamics. The system dynamics identified with the network are the Mach number dynamics of the 16 Foot Transonic Tunnel at NASA Langley Research Center, Hampton, Virginia. The training data spans an operating range of Mach numbers from 0.4 to 1.3.

  1. Adaptive Systems in Education: A Review and Conceptual Unification

    ERIC Educational Resources Information Center

    Wilson, Chunyu; Scott, Bernard

    2017-01-01

    Purpose: The purpose of this paper is to review the use of adaptive systems in education. It is intended to be a useful introduction for the non-specialist reader. Design/methodology/approach: A distinction is made between intelligent tutoring systems (ITSs) and adaptive hypermedia systems (AHSs). The two kinds of system are defined, compared and…

  2. Nonlinear vibrating system identification via Hilbert decomposition

    NASA Astrophysics Data System (ADS)

    Feldman, Michael; Braun, Simon

    2017-02-01

    This paper deals with the identification of nonlinear vibration systems, based on measured signals for free and forced vibration regimes. Two categories of time domain signal are analyzed, one of a fast inter-modulation signal and a second as composed of several mono-components. To some extent, this attempts to imitate analytic studies of such systems, with its two major analysis groups - the perturbation and the harmonic balance methods. Two appropriate signal processing methods are then investigated, one based on demodulation and the other on signal decomposition. The Hilbert Transform (HT) has been shown to enable effective and simple methods of analysis. We show that precise identification of the nonlinear parameters can be obtained, contrary to other average HT based methods where only approximation parameters are obtained. The effectiveness of the proposed methods is demonstrated for the precise nonlinear system identification, using both the signal demodulation and the signal decomposition methods. Following the exposition of the tools used, both the signal demodulation as well as decomposition are applied to classical examples of nonlinear systems. Cases of nonlinear stiffness and damping forces are analyzed. These include, among other, an asymmetric Helmholtz oscillator, a backlash with nonlinear turbulent square friction, and a Duffing oscillator with dry friction.

  3. In Silico and Biochemical Analysis of Physcomitrella patens Photosynthetic Antenna: Identification of Subunits which Evolved upon Land Adaptation

    PubMed Central

    Alboresi, Alessandro; Caffarri, Stefano; Nogue, Fabien; Bassi, Roberto; Morosinotto, Tomas

    2008-01-01

    Background In eukaryotes the photosynthetic antenna system is composed of subunits encoded by the light harvesting complex (Lhc) multigene family. These proteins play a key role in photosynthesis and are involved in both light harvesting and photoprotection. The moss Physcomitrella patens is a member of a lineage that diverged from seed plants early after land colonization and therefore by studying this organism, we may gain insight into adaptations to the aerial environment. Principal Findings In this study, we characterized the antenna protein multigene family in Physcomitrella patens, by sequence analysis as well as biochemical and functional investigations. Sequence identification and analysis showed that some antenna polypeptides, such as Lhcb3 and Lhcb6, are present only in land organisms, suggesting they play a role in adaptation to the sub-aerial environment. Our functional analysis which showed that photo-protective mechanisms in Physcomitrella patens are very similar to those in seed plants fits with this hypothesis. In particular, Physcomitrella patens also activates Non Photochemical Quenching upon illumination, consistent with the detection of an ortholog of the PsbS protein. As a further adaptation to terrestrial conditions, the content of Photosystem I low energy absorbing chlorophylls also increased, as demonstrated by differences in Lhca3 and Lhca4 polypeptide sequences, in vitro reconstitution experiments and low temperature fluorescence spectra. Conclusions This study highlights the role of Lhc family members in environmental adaptation and allowed proteins associated with mechanisms of stress resistance to be identified within this large family. PMID:18446222

  4. Unique device identification system. Final rule.

    PubMed

    2013-09-24

    The Food and Drug Administration (FDA) is issuing a final rule to establish a system to adequately identify devices through distribution and use. This rule requires the label of medical devices to include a unique device identifier (UDI), except where the rule provides for an exception or alternative placement. The labeler must submit product information concerning devices to FDA's Global Unique Device Identification Database (GUDID), unless subject to an exception or alternative. The system established by this rule requires the label and device package of each medical device to include a UDI and requires that each UDI be provided in a plain-text version and in a form that uses automatic identification and data capture (AIDC) technology. The UDI will be required to be directly marked on the device itself if the device is intended to be used more than once and intended to be reprocessed before each use.

  5. Ladder Forms in Estimation and System Identification.

    DTIC Science & Technology

    1977-01-01

    system identification . Many record applications, such as in geophysical signal processing, high resolution (’maximum entropy’) spectral estimation and speech encoding, justify the interest in these forms. They appear in many contexts, such as scattering and network theory and the theory of orthogonal polynomials. The state-space model ladder realizations are very closely related in (block) Schwarz matrix canonical forms, which generally appear in the context of stability analysis. In fact they are the natural ’stability canonical form’ for

  6. 77 FR 40735 - Unique Device Identification System

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-07-10

    ...The Food and Drug Administration (FDA) is proposing to establish a unique device identification system to implement the requirement added to the Federal Food, Drug, and Cosmetic Act (FD&C Act) by section 226 of the Food and Drug Administration Amendments Act of 2007 (FDAAA), Section 226 of FDAAA amended the FD&C Act to add new section 519(f), which directs FDA to promulgate regulations......

  7. Identification of dynamic systems, theory and formulation

    NASA Technical Reports Server (NTRS)

    Maine, R. E.; Iliff, K. W.

    1985-01-01

    The problem of estimating parameters of dynamic systems is addressed in order to present the theoretical basis of system identification and parameter estimation in a manner that is complete and rigorous, yet understandable with minimal prerequisites. Maximum likelihood and related estimators are highlighted. The approach used requires familiarity with calculus, linear algebra, and probability, but does not require knowledge of stochastic processes or functional analysis. The treatment emphasizes unification of the various areas in estimation in dynamic systems is treated as a direct outgrowth of the static system theory. Topics covered include basic concepts and definitions; numerical optimization methods; probability; statistical estimators; estimation in static systems; stochastic processes; state estimation in dynamic systems; output error, filter error, and equation error methods of parameter estimation in dynamic systems, and the accuracy of the estimates.

  8. The ALICE-HMPID Detector Control System: Its evolution towards an expert and adaptive system

    NASA Astrophysics Data System (ADS)

    De Cataldo, G.; Franco, A.; Pastore, C.; Sgura, I.; Volpe, G.

    2011-05-01

    The High Momentum Particle IDentification (HMPID) detector is a proximity focusing Ring Imaging Cherenkov (RICH) for charged hadron identification. The HMPID is based on liquid C 6F 14 as the radiator medium and on a 10 m 2 CsI coated, pad segmented photocathode of MWPCs for UV Cherenkov photon detection. To ensure full remote control, the HMPID is equipped with a detector control system (DCS) responding to industrial standards for robustness and reliability. It has been implemented using PVSS as Slow Control And Data Acquisition (SCADA) environment, Programmable Logic Controller as control devices and Finite State Machines for modular and automatic command execution. In the perspective of reducing human presence at the experiment site, this paper focuses on DCS evolution towards an expert and adaptive control system, providing, respectively, automatic error recovery and stable detector performance. HAL9000, the first prototype of the HMPID expert system, is then presented. Finally an analysis of the possible application of the adaptive features is provided.

  9. Assessing Psychological Functioning in Metabolic Disorders: Validation of the Adaptive Behavior Assessment System, Second Edition (ABAS-II), and the Behavior Rating Inventory of Executive Function (BRIEF) for Identification of Individuals at Risk.

    PubMed

    Waisbren, Susan E; He, Jianping; McCarter, Robert

    2015-01-01

    Long-term follow-up of neuropsychological functioning in metabolic disorders remains difficult due to limited opportunities for comprehensive neuropsychological evaluations. This study examined the validity of using the Adaptive Behavior Assessment System, Second Edition (ABAS-II), and the Behavior Rating Inventory of Executive Function (BRIEF) for assessing developmental status in metabolic disorders and for identifying individuals at risk for cognitive deficits. Results from individuals with urea cycle disorders, phenylketonuria, galactosemia, and fatty acid oxidation disorders were obtained on the ABAS-II and BRIEF and were compared to results obtained from neuropsychological testing performed on the same day. Correlations between scores on the ABAS-II and developmental or IQ tests for individuals with urea cycle disorders ranged from 0.48 to 0.72 and concordance rates for scores greater than a standard deviation below the normative mean ranged from 69 to 89%. Correlations ranged from 0.20 to 0.68 with concordance ranging from 73 to 90% in the other metabolic disorders. For the BRIEF, correlations with other tests of executive functioning were significant for urea cycle disorders, with concordance ranging from 52 to 80%. For the other metabolic disorders, correlations ranged from -0.09 to -0.55. Concordance rates for at-risk status on the BRIEF and executive functioning tests ranged from 55% in adults to 80% in children with other metabolic disorders. These results indicate that the ABAS-II and BRIEF together can confidently be used as an adjunct or supplementary method for clinical follow-up and for research on functional status involving infants, children, and adults with metabolic disorders.

  10. Integration of the immune system: a complex adaptive supersystem

    NASA Astrophysics Data System (ADS)

    Crisman, Mark V.

    2001-10-01

    Immunity to pathogenic organisms is a complex process involving interacting factors within the immune system including circulating cells, tissues and soluble chemical mediators. Both the efficiency and adaptive responses of the immune system in a dynamic, often hostile, environment are essential for maintaining our health and homeostasis. This paper will present a brief review of one of nature's most elegant, complex adaptive systems.

  11. Implementation of an Adaptive Learning System Using a Bayesian Network

    ERIC Educational Resources Information Center

    Yasuda, Keiji; Kawashima, Hiroyuki; Hata, Yoko; Kimura, Hiroaki

    2015-01-01

    An adaptive learning system is proposed that incorporates a Bayesian network to efficiently gauge learners' understanding at the course-unit level. Also, learners receive content that is adapted to their measured level of understanding. The system works on an iPad via the Edmodo platform. A field experiment using the system in an elementary school…

  12. Wiener-Hammerstein system identification - an evolutionary approach

    NASA Astrophysics Data System (ADS)

    Naitali, Abdessamad; Giri, Fouad

    2016-01-01

    The problem of identifying parametric Wiener-Hammerstein (WH) systems is addressed within the evolutionary optimisation context. Specifically, a hybrid culture identification method is developed that involves model structure adaptation using genetic recombination and model parameter learning using particle swarm optimisation. The method enjoys three interesting features: (1) the risk of premature convergence of model parameter estimates to local optima is significantly reduced, due to the constantly maintained diversity of model candidates; (2) no prior knowledge is needed except for upper bounds on the system structure indices; (3) the method is fully autonomous as no interaction is needed with the user during the optimum search process. The performances of the proposed method will be illustrated and compared to alternative methods using a well-established WH benchmark.

  13. Isoplanatism in a multiconjugate adaptive optics system.

    PubMed

    Tokovinin, A; Le Louarn, M; Sarazin, M

    2000-10-01

    Turbulence correction in a large field of view by use of an adaptive optics imaging system with several deformable mirrors (DM's) conjugated to various heights is considered. The residual phase variance is computed for an optimized linear algorithm in which a correction of each turbulent layer is achieved by applying a combination of suitably smoothed and scaled input phase screens to all DM's. Finite turbulence outer scale and finite spatial resolution of the DM's are taken into account. A general expression for the isoplanatic angle thetaM of a system with M mirrors is derived in the limiting case of infinitely large apertures and Kolmogorov turbulence. Like Fried's isoplanatic angle theta0,thetaM is a function only of the turbulence vertical profile, is scalable with wavelength, and is independent of the telescope diameter. Use of angle thetaM permits the gain in the field of view due to the increased number of DM's to be quantified and their optimal conjugate heights to be found. Calculations with real turbulence profiles show that with three DM's a gain of 7-10x is possible, giving the typical and best isoplanatic field-of-view radii of 16 and 30 arcseconds, respectively, at lambda = 0.5 microm. It is shown that in the actual systems the isoplanatic field will be somewhat larger than thetaM owing to the combined effects of finite aperture diameter, finite outer scale, and optimized wave-front spatial filtering. However, this additional gain is not dramatic; it is less than 1.5x for large-aperture telescopes.

  14. Realization-Based System Identification with Applications

    NASA Astrophysics Data System (ADS)

    Miller, Daniel N.

    The identification of dynamic system behavior from experimentally measured or computationally simulated data is fundamental to the fields of control system design, modal analysis, and defect detection. In this dissertation, methods for system identification are developed based on classical linear system realization theory. The common methods of state-space realization from a measured, discrete-time impulse response are generalized to the following additional types of experiments: measured step responses, arbitrary sets of input-output data, and estimated cross-covariance functions of input-output data. The methods are particularly well suited to systems with large input and/or output dimension, for which classical system identification methods based on maximum likelihood estimation may fail due to their reliance on non-convex optimizations. The realization-based methods by themselves require a finite number of linear algebraic operations. Because these methods implicitly optimize cost functions that are linear in state-space parameters, they may be augmented with convex constraints to form convex optimization problems. Several common behavioral constraints are translated into eigenvalue constraints stated as linear matrix inequalities, and the realization-based methods are converted into semidefinite programming problems. Some additional constraints on transient and steady-state behavior are derived and incorporated into a quadratic program, which is solved following the semidefinite program. The newly developed realization-based methods are applied to two experiments: the aeroelastic response of a fighter aircraft and the transient thermal behavior of a light-emitting diode. The algorithms for each experiment are implemented in two freely available software packages.

  15. Power system identification toolbox: Phase two progress

    SciTech Connect

    Trudnowski, D.J.

    1994-08-01

    This report describes current progress on a project funded by the Bonneville Power Administration (BPA) to develop a set of state-of-the-art analysis software (termed the Power System Identification [PSI] Toolbox) for fitting dynamic models to measured data. The project is being conducted as a three-phase effort. The first phase, completed in late 1992, involved investigating the characteristics of the analysis techniques by evaluating existing software and developing guidelines for best use. Phase Two includes extending current software, developing new analysis algorithms and software, and demonstrating and developing applications. The final phase will focus on reorganizing the software into a modular collection of documented computer programs and developing user manuals with instruction and application guidelines. Phase Two is approximately 50% complete; progress to date and a vision for the final product of the PSI Toolbox are described. The needs of the power industry for specialized system identification methods are particularly acute. The industry is currently pushing to operate transmission systems much closer to theoretical limits by using real-time, large-scale control systems to dictate power flows and maintain dynamic stability. Reliably maintaining stability requires extensive system-dynamic modeling and analysis capability, including measurement-based methods. To serve this need, the BPA has developed specialized system-identification computer codes through in-house efforts and university contract research over the last several years. To make full integrated use of the codes, as well as other techniques, the BPA has commissioned Pacific Northwest Laboratory (PNL) to further develop the codes and techniques into the PSI Toolbox.

  16. Intellectual system of identification of Arabic graphics

    NASA Astrophysics Data System (ADS)

    Abdoullayeva, Gulchin G.; Aliyev, Telman A.; Gurbanova, Nazakat G.

    2001-08-01

    The studies made by using the domain of graphic images allowed creating facilities of the artificial intelligence for letters, letter combinations etc. for various graphics and prints. The work proposes a system of recognition and identification of symbols of the Arabic graphics, which has its own specificity as compared to Latin and Cyrillic ones. The starting stage of the recognition and the identification is coding with further entry of information into a computer. Here the problem of entry is one of the essentials. For entry of a large volume of information in the unit of time a scanner is usually employed. Along with the scanner the authors suggest their elaboration of technical facilities for effective input and coding of the information. For refinement of symbols not identified from the scanner mostly for a small bulk of information the developed coding devices are used directly in the process of writing. The functional design of the software is elaborated on the basis of the heuristic model of the creative activity of a researcher and experts in the description and estimation of states of the weakly formalizable systems on the strength of the methods of identification and of selection of geometric features.

  17. Injectable electronic identification, monitoring, and stimulation systems.

    PubMed

    Troyk, P R

    1999-01-01

    Historically, electronic devices such as pacemakers and neuromuscular stimulators have been surgically implanted into animals and humans. A new class of implants made possible by advances in monolithic electronic design and implant packaging is small enough to be implanted by percutaneous injection through large-gauge hypodermic needles and does not require surgical implantation. Among these, commercially available implants, known as radio frequency identification (RFID) tags, are used for livestock, pet, laboratory animal, and endangered-species identification. The RFID tag is a subminiature glass capsule containing a solenoidal coil and an integrated circuit. Acting as the implanted half of a transcutaneous magnetic link, the RFID tag is powered by and communicates with an extracorporeal magnetic reader. The tag transmits a unique identification code that serves the function of identifying the animal. Millions of RFID tags have been sold since the early 1980s. Based on the success of the RFID tags, research laboratories have developed injectable medical implants, known as micromodules. One type of micromodule, the microstimulator, is designed for use in functional-neuromuscular stimulation. Each microstimulator is uniquely addressable and could comprise one channel of a multichannel functional-neuromuscular stimulation system. Using bidirectional telemetry and commands, from a single extracorporeal transmitter, as many as 256 microstimulators could form the hardware basis for a complex functional-neuromuscular stimulation feedback-control system. Uses include stimulation of paralyzed muscle, therapeutic functional-neuromuscular stimulation, and neuromodulatory functions such as laryngeal stimulation and sleep apnea.

  18. Network and adaptive system of systems modeling and analysis.

    SciTech Connect

    Lawton, Craig R.; Campbell, James E. Dr.; Anderson, Dennis James; Eddy, John P.

    2007-05-01

    This report documents the results of an LDRD program entitled ''Network and Adaptive System of Systems Modeling and Analysis'' that was conducted during FY 2005 and FY 2006. The purpose of this study was to determine and implement ways to incorporate network communications modeling into existing System of Systems (SoS) modeling capabilities. Current SoS modeling, particularly for the Future Combat Systems (FCS) program, is conducted under the assumption that communication between the various systems is always possible and occurs instantaneously. A more realistic representation of these communications allows for better, more accurate simulation results. The current approach to meeting this objective has been to use existing capabilities to model network hardware reliability and adding capabilities to use that information to model the impact on the sustainment supply chain and operational availability.

  19. Valuation of design adaptability in aerospace systems

    NASA Astrophysics Data System (ADS)

    Fernandez Martin, Ismael

    As more information is brought into early stages of the design, more pressure is put on engineers to produce a reliable, high quality, and financially sustainable product. Unfortunately, requirements established at the beginning of a new project by customers, and the environment that surrounds them, continue to change in some unpredictable ways. The risk of designing a system that may become obsolete during early stages of production is currently tackled by the use of robust design simulation, a method that allows to simultaneously explore a plethora of design alternatives and requirements with the intention of accounting for uncertain factors in the future. Whereas this design technique has proven to be quite an improvement in design methods, under certain conditions, it fails to account for the change of uncertainty over time and the intrinsic value embedded in the system when certain design features are activated. This thesis introduces the concepts of adaptability and real options to manage risk foreseen in the face of uncertainty at early design stages. The method described herein allows decision-makers to foresee the financial impact of their decisions at the design level, as well as the final exposure to risk. In this thesis, cash flow models, traditionally used to obtain the forecast of a project's value over the years, were replaced with surrogate models that are capable of showing fluctuations on value every few days. This allowed a better implementation of real options valuation, optimization, and strategy selection. Through the option analysis model, an optimization exercise allows the user to obtain the best implementation strategy in the face of uncertainty as well as the overall value of the design feature. Here implementation strategy refers to the decision to include a new design feature in the system, after the design has been finalized, but before the end of its production life. The ability to do this in a cost efficient manner after the system

  20. Cascaded Effects of Spatial Adaptation in the Early Visual System

    PubMed Central

    Dhruv, Neel T.; Carandini, Matteo

    2014-01-01

    Summary Virtually all stages of the visual system exhibit adaptation: neurons adjust their responses based on the recent stimulus history. While some of these adjustments occur at specific stages, others may be inherited from earlier stages. How do adaptation effects cascade along the visual system? We measured spatially selective adaptation at two successive stages in the mouse visual system: visual thalamus (LGN) and primary visual cortex (V1). This form of adaptation affected both stages but in drastically different ways: in LGN it only changed response gain, while in V1 it also shifted spatial tuning away from the adaptor. These effects, however, are reconciled by a simple model whereby V1 neurons summate LGN inputs with a fixed, unadaptable weighting profile. These results indicate that adaptation effects cascade through the visual system, that this cascading can shape selectivity, and that the rules of integration from one stage to the next are not themselves adaptable. PMID:24507190

  1. Cascaded effects of spatial adaptation in the early visual system.

    PubMed

    Dhruv, Neel T; Carandini, Matteo

    2014-02-05

    Virtually all stages of the visual system exhibit adaptation: neurons adjust their responses based on the recent stimulus history. While some of these adjustments occur at specific stages, others may be inherited from earlier stages. How do adaptation effects cascade along the visual system? We measured spatially selective adaptation at two successive stages in the mouse visual system: visual thalamus (LGN) and primary visual cortex (V1). This form of adaptation affected both stages but in drastically different ways: in LGN it only changed response gain, while in V1 it also shifted spatial tuning away from the adaptor. These effects, however, are reconciled by a simple model whereby V1 neurons summate LGN inputs with a fixed, unadaptable weighting profile. These results indicate that adaptation effects cascade through the visual system, that this cascading can shape selectivity, and that the rules of integration from one stage to the next are not themselves adaptable.

  2. Central nervous system adaptation to exercise training

    NASA Astrophysics Data System (ADS)

    Kaminski, Lois Anne

    Exercise training causes physiological changes in skeletal muscle that results in enhanced performance in humans and animals. Despite numerous studies on exercise effects on skeletal muscle, relatively little is known about adaptive changes in the central nervous system. This study investigated whether spinal pathways that mediate locomotor activity undergo functional adaptation after 28 days of exercise training. Ventral horn spinal cord expression of calcitonin gene-related peptide (CGRP), a trophic factor at the neuromuscular junction, choline acetyltransferase (Chat), the synthetic enzyme for acetylcholine, vesicular acetylcholine transporter (Vacht), a transporter of ACh into synaptic vesicles and calcineurin (CaN), a protein phosphatase that phosphorylates ion channels and exocytosis machinery were measured to determine if changes in expression occurred in response to physical activity. Expression of these proteins was determined by western blot and immunohistochemistry (IHC). Comparisons between sedentary controls and animals that underwent either endurance training or resistance training were made. Control rats received no exercise other than normal cage activity. Endurance-trained rats were exercised 6 days/wk at 31m/min on a treadmill (8% incline) for 100 minutes. Resistance-trained rats supported their weight plus an additional load (70--80% body weight) on a 60° incline (3 x 3 min, 5 days/wk). CGRP expression was measured by radioimmunoassay (RIA). CGRP expression in the spinal dorsal and ventral horn of exercise-trained animals was not significantly different than controls. Chat expression measured by Western blot and IHC was not significantly different between runners and controls but expression in resistance-trained animals assayed by IHC was significantly less than controls and runners. Vacht and CaN immunoreactivity in motor neurons of endurance-trained rats was significantly elevated relative to control and resistance-trained animals. Ventral

  3. Aircraft as adaptive nonlinear system which must be in the adaptational maximum zone for safety

    SciTech Connect

    Ignative, M.; Simatos, N.; Sivasundaram, S.

    1994-12-31

    Safety is a main problem in aircraft. We are considering this problem from the point of view related to existence of the adaptational maximum in complex developing systems. Safety space of aircraft parameters are determined. This space is transformed to different regimes of flight, when one engine malfunctions etc., are considered. Also it is shown that maximum safety is in adaptational maximum zone.

  4. CRISPR adaptation in Escherichia coli subtypeI-E system.

    PubMed

    Kiro, Ruth; Goren, Moran G; Yosef, Ido; Qimron, Udi

    2013-12-01

    The CRISPRs (clustered regularly interspaced short palindromic repeats) and their associated Cas (CRISPR-associated) proteins are a prokaryotic adaptive defence system against foreign nucleic acids. The CRISPR array comprises short repeats flanking short segments, called 'spacers', which are derived from foreign nucleic acids. The process of spacer insertion into the CRISPR array is termed 'adaptation'. Adaptation allows the system to rapidly evolve against emerging threats. In the present article, we review the most recent studies on the adaptation process, and focus primarily on the subtype I-E CRISPR-Cas system of Escherichia coli.

  5. Adapt

    NASA Astrophysics Data System (ADS)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  6. Robust uncertainty evaluation for system identification on distributed wireless platforms

    NASA Astrophysics Data System (ADS)

    Crinière, Antoine; Döhler, Michael; Le Cam, Vincent; Mevel, Laurent

    2016-04-01

    Health monitoring of civil structures by system identification procedures from automatic control is now accepted as a valid approach. These methods provide frequencies and modeshapes from the structure over time. For a continuous monitoring the excitation of a structure is usually ambient, thus unknown and assumed to be noise. Hence, all estimates from the vibration measurements are realizations of random variables with inherent uncertainty due to (unknown) process and measurement noise and finite data length. The underlying algorithms are usually running under Matlab under the assumption of large memory pool and considerable computational power. Even under these premises, computational and memory usage are heavy and not realistic for being embedded in on-site sensor platforms such as the PEGASE platform. Moreover, the current push for distributed wireless systems calls for algorithmic adaptation for lowering data exchanges and maximizing local processing. Finally, the recent breakthrough in system identification allows us to process both frequency information and its related uncertainty together from one and only one data sequence, at the expense of computational and memory explosion that require even more careful attention than before. The current approach will focus on presenting a system identification procedure called multi-setup subspace identification that allows to process both frequencies and their related variances from a set of interconnected wireless systems with all computation running locally within the limited memory pool of each system before being merged on a host supervisor. Careful attention will be given to data exchanges and I/O satisfying OGC standards, as well as minimizing memory footprints and maximizing computational efficiency. Those systems are built in a way of autonomous operations on field and could be later included in a wide distributed architecture such as the Cloud2SM project. The usefulness of these strategies is illustrated on

  7. Nonequilibrium Enhances Adaptation Efficiency of Stochastic Biochemical Systems

    PubMed Central

    Jia, Chen; Qian, Minping

    2016-01-01

    Adaptation is a crucial biological function possessed by many sensory systems. Early work has shown that some influential equilibrium models can achieve accurate adaptation. However, recent studies indicate that there are close relationships between adaptation and nonequilibrium. In this paper, we provide an explanation of these two seemingly contradictory results based on Markov models with relatively simple networks. We show that as the nonequilibrium driving becomes stronger, the system under consideration will undergo a phase transition along a fixed direction: from non-adaptation to simple adaptation then to oscillatory adaptation, while the transition in the opposite direction is forbidden. This indicates that although adaptation may be observed in equilibrium systems, it tends to occur in systems far away from equilibrium. In addition, we find that nonequilibrium will improve the performance of adaptation by enhancing the adaptation efficiency. All these results provide a deeper insight into the connection between adaptation and nonequilibrium. Finally, we use a more complicated network model of bacterial chemotaxis to validate the main results of this paper. PMID:27195482

  8. Identification of system misregistrations during AO-corrected observations

    NASA Astrophysics Data System (ADS)

    Béchet, C.; Thiébaut, É.; .; Tallon, M.; Kolb, J.; Madec, P.-Y.

    2011-09-01

    The E-ELT will be equipped with a deformable mirror inside the telescope. The performance of reconstruction and control depends on the calibration of the interaction matrix- or a model of the interaction matrix- , which characterizes the system and the relationship between the commands sent to the deformable mirrors (DM) and the wavefront sensors (WFS) slopes. Such a calibration will be more complex than for the current systems at the VLT since it will have to be at least partly measured on sky and for a much larger number of degrees of freedom (more than 5000). In addition, gravity or temperature variations for instance are likely to introduce slow evolution of the matching between the M4 Deformable mirror and the WFS geometry. This can occur during observations and therefore degrade the adaptive optics (AO) correction. To relax the need of frequent painful calibrations and to prevent a loss of performance due to misregistrations, we investigate how to track the evolution of the interaction matrix errors in closed-loop without introducing any degradation in the observations. This is done thanks to identification methods and optimization theory. First, we formally describe the problem and the difficulties of such an identification in closed-loop configuration. Then, we present 2 solutions, based on the optimization of the error of estimates of the WFS slopes, at the output of the closed-loop AO. The performance of the methods and their limitations are discussed formally and thanks to numerical simulations of a high order AO system. We finally explore to which extent these methods currently studied for the Adaptive Optics Facility (AOF) at the VLT can be applied to the E-ELT.

  9. Boundedness of the solutions for certain classes of fractional differential equations with application to adaptive systems.

    PubMed

    Aguila-Camacho, Norelys; Duarte-Mermoud, Manuel A

    2016-01-01

    This paper presents the analysis of three classes of fractional differential equations appearing in the field of fractional adaptive systems, for the case when the fractional order is in the interval α ∈(0,1] and the Caputo definition for fractional derivatives is used. The boundedness of the solutions is proved for all three cases, and the convergence to zero of the mean value of one of the variables is also proved. Applications of the obtained results to fractional adaptive schemes in the context of identification and control problems are presented at the end of the paper, including numerical simulations which support the analytical results.

  10. Automated Firearms Identification System (AFIDS), phase 1

    NASA Technical Reports Server (NTRS)

    Blackwell, R. J.; Framan, E. P.

    1974-01-01

    Items critical to the future development of an automated firearms identification system (AFIDS) have been examined, with the following specific results: (1) Types of objective data, that can be utilized to help establish a more factual basis for determining identity and nonidentity between pairs of fired bullets, have been identified. (2) A simulation study has indicated that randomly produced lines, similar in nature to the individual striations on a fired bullet, can be modeled and that random sequences, when compared to each other, have predictable relationships. (3) A schematic diagram of the general concept for AFIDS has been developed and individual elements of this system have been briefly tested for feasibility. Future implementation of such a proposed system will depend on such factors as speed, utility, projected total cost and user requirements for growth. The success of the proposed system, when operational, would depend heavily on existing firearms examiners.

  11. Black-box identification of a class of nonlinear systems by a recurrent neurofuzzy network.

    PubMed

    Gonzalez-Olvera, Marcos A; Tang, Yu

    2010-04-01

    This brief presents a structure for black-box identification based on continuous-time recurrent neurofuzzy networks for a class of dynamic nonlinear systems. The proposed network catches the dynamics of a system by generating its own states, using only input and output measurements of the system. The training algorithm is based on adaptive observer theory, the stability of the network, the convergence of the training algorithm, and the ultimate bound on the identification error as well as the parameter error are established. Experimental results are included to illustrate the effectiveness of the proposed method.

  12. A novel algorithm for real-time adaptive signal detection and identification

    SciTech Connect

    Sleefe, G.E.; Ladd, M.D.; Gallegos, D.E.; Sicking, C.W.; Erteza, I.A.

    1998-04-01

    This paper describes a novel digital signal processing algorithm for adaptively detecting and identifying signals buried in noise. The algorithm continually computes and updates the long-term statistics and spectral characteristics of the background noise. Using this noise model, a set of adaptive thresholds and matched digital filters are implemented to enhance and detect signals that are buried in the noise. The algorithm furthermore automatically suppresses coherent noise sources and adapts to time-varying signal conditions. Signal detection is performed in both the time-domain and the frequency-domain, thereby permitting the detection of both broad-band transients and narrow-band signals. The detection algorithm also provides for the computation of important signal features such as amplitude, timing, and phase information. Signal identification is achieved through a combination of frequency-domain template matching and spectral peak picking. The algorithm described herein is well suited for real-time implementation on digital signal processing hardware. This paper presents the theory of the adaptive algorithm, provides an algorithmic block diagram, and demonstrate its implementation and performance with real-world data. The computational efficiency of the algorithm is demonstrated through benchmarks on specific DSP hardware. The applications for this algorithm, which range from vibration analysis to real-time image processing, are also discussed.

  13. Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems

    NASA Astrophysics Data System (ADS)

    Williams, Rube B.

    2004-02-01

    Control law adaptation that includes implicit or explicit adaptive state estimation, can be a fundamental underpinning for the success of intelligent control in complex systems, particularly during subsystem failures, where vital system states and parameters can be impractical or impossible to measure directly. A practical algorithm is proposed for adaptive state filtering and control in nonlinear dynamic systems when the state equations are unknown or are too complex to model analytically. The state equations and inverse plant model are approximated by using neural networks. A framework for a neural network based nonlinear dynamic inversion control law is proposed, as an extrapolation of prior developed restricted complexity methodology used to formulate the adaptive state filter. Examples of adaptive filter performance are presented for an SSME simulation with high pressure turbine failure to support extrapolations to adaptive control problems.

  14. Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems

    SciTech Connect

    Williams, Rube B.

    2004-02-04

    Control law adaptation that includes implicit or explicit adaptive state estimation, can be a fundamental underpinning for the success of intelligent control in complex systems, particularly during subsystem failures, where vital system states and parameters can be impractical or impossible to measure directly. A practical algorithm is proposed for adaptive state filtering and control in nonlinear dynamic systems when the state equations are unknown or are too complex to model analytically. The state equations and inverse plant model are approximated by using neural networks. A framework for a neural network based nonlinear dynamic inversion control law is proposed, as an extrapolation of prior developed restricted complexity methodology used to formulate the adaptive state filter. Examples of adaptive filter performance are presented for an SSME simulation with high pressure turbine failure to support extrapolations to adaptive control problems.

  15. Concept Based Approach for Adaptive Personalized Course Learning System

    ERIC Educational Resources Information Center

    Salahli, Mehmet Ali; Özdemir, Muzaffer; Yasar, Cumali

    2013-01-01

    One of the most important factors for improving the personalization aspects of learning systems is to enable adaptive properties to them. The aim of the adaptive personalized learning system is to offer the most appropriate learning path and learning materials to learners by taking into account their profiles. In this paper, a new approach to…

  16. Adaptive tracking control for a class of uncertain chaotic systems

    NASA Astrophysics Data System (ADS)

    Chen, Feng-Xiang; Wang, Wei; Zhang, Wei-Dong

    2007-09-01

    The paper is concerned with adaptive tracking problem for a class of chaotic system with time-varying uncertainty, but bounded by norm polynomial. Based on adaptive technique, it proposes a novel controller to asymptotically track the arbitrary desired bounded trajectory. Simulation on the Rossler chaotic system is performed and the result verifies the effectiveness of the proposed method.

  17. Development of Adaptive Kanji Learning System for Mobile Phone

    ERIC Educational Resources Information Center

    Li, Mengmeng; Ogata, Hiroaki; Hou, Bin; Hashimoto, Satoshi; Liu, Yuqin; Uosaki, Noriko; Yano, Yoneo

    2010-01-01

    This paper describes an adaptive learning system based on mobile phone email to support the study of Japanese Kanji. In this study, the main emphasis is on using the adaptive learning to resolve one common problem of the mobile-based email or SMS language learning systems. To achieve this goal, the authors main efforts focus on three aspects:…

  18. Adaptive Hypermedia Educational System Based on XML Technologies.

    ERIC Educational Resources Information Center

    Baek, Yeongtae; Wang, Changjong; Lee, Sehoon

    This paper proposes an adaptive hypermedia educational system using XML technologies, such as XML, XSL, XSLT, and XLink. Adaptive systems are capable of altering the presentation of the content of the hypermedia on the basis of a dynamic understanding of the individual user. The user profile can be collected in a user model, while the knowledge…

  19. Management Strategies for Complex Adaptive Systems: Sensemaking, Learning, and Improvisation

    ERIC Educational Resources Information Center

    McDaniel, Reuben R., Jr.

    2007-01-01

    Misspecification of the nature of organizations may be a major reason for difficulty in achieving performance improvement. Organizations are often viewed as machine-like, but complexity science suggests that organizations should be viewed as complex adaptive systems. I identify the characteristics of complex adaptive systems and give examples of…

  20. Adaptable System for Vehicle Health and Usage Monitoring

    NASA Technical Reports Server (NTRS)

    Woodart, Stanley E.; Woodman, Keith L.; Coffey, Neil C.; Taylor, Bryant D.

    2005-01-01

    Aircraft and other vehicles are often kept in service beyond their original design lives. As they age, they become susceptible to system malfunctions and fatigue. Unlike future aircraft that will include health-monitoring capabilities as integral parts in their designs, older aircraft have not been so equipped. The Adaptable Vehicle Health and Usage Monitoring System is designed to be retrofitted into a preexisting fleet of military and commercial aircraft, ships, or ground vehicles to provide them with state-of-the-art health- and usage-monitoring capabilities. The monitoring system is self-contained, and the integration of it into existing systems entails limited intrusion. In essence, it has bolt-on/ bolt-off simplicity that makes it easy to install on any preexisting vehicle or structure. Because the system is completely independent of the vehicle, it can be certified for airworthiness as an independent system. The purpose served by the health-monitoring system is to reduce vehicle operating costs and to increase safety and reliability. The monitoring system is a means to identify damage to, or deterioration of, vehicle subsystems, before such damage or deterioration becomes costly and/or disastrous. Frequent monitoring of a vehicle enables identification of the embryonic stages of damage or deterioration. The knowledge thus gained can be used to correct anomalies while they are still somewhat minor. Maintenance can be performed as needed, instead of having the need for maintenance identified during cyclic inspections that take vehicles off duty even when there are no maintenance problems. Measurements and analyses acquired by the health-monitoring system also can be used to analyze mishaps. Overall, vehicles can be made more reliable and kept on duty for longer times. Figure 1 schematically depicts the system as applied to a fleet of n vehicles. The system has three operational levels. All communication between system components is by use of wireless

  1. Sinusoidal error perturbation reveals multiple coordinate systems for sensorymotor adaptation

    PubMed Central

    Hudson, Todd E.; Landy, Michael S.

    2016-01-01

    A coordinate system is composed of an encoding, defining the dimensions of the space, and an origin. We examine the coordinate encoding used to update motor plans during sensory-motor adaptation to center-out reaches. Adaptation is induced using a novel paradigm in which feedback of reach endpoints is perturbed following a sinewave pattern over trials; the perturbed dimensions of the feedback were the axes of a Cartesian coordinate system in one session and a polar coordinate system in another session. For center-out reaches to randomly chosen target locations, reach errors observed at one target will require different corrections at other targets within Cartesian- and polar-coded systems. The sinewave adaptation technique allowed us to simultaneously adapt both dimensions of each coordinate system (x-y, or reach gain and angle), and identify the contributions of each perturbed dimension by adapting each at a distinct temporal frequency. The efficiency of this technique further allowed us to employ perturbations that were a fraction the size normally used, which avoids confounding automatic adaptive processes with deliberate adjustments made in response to obvious experimental manipulations. Subjects independently corrected errors in each coordinate in both sessions, suggesting that the nervous system encodes both a Cartesian- and polar-coordinate-based internal representation for motor adaptation. The gains and phase lags of the adaptive responses are not readily explained by current theories of sensory-motor adaptation. Motor adaptation is fundamental to the neural control of movement, affording an automatic process to maintain a consistent relationship between motor plans and movement outcomes. That is, adaptation is described as updating an internal mapping between desired motor outcome and motor output (Sanger, 2004; Shadmehr, Smith, & Krakauer, 2010), not a deliberate corrective action. Here, using a method that relies on extremely small perturbations that

  2. Parameter identification for nonlinear aerodynamic systems

    NASA Technical Reports Server (NTRS)

    Pearson, Allan E.

    1993-01-01

    This final technical report covers a three and one-half year period preceding February 28, 1993 during which support was provided under NASA Grant NAG-1-1065. Following a general description of the system identification problem and a brief survey of methods to attack it, the basic ideas behind the approach taken in this research effort are presented. The results obtained are described with reference to the published work, including the five semiannual progress reports previously submitted and two interim technical reports.

  3. Calibrated Methodology for Assessing Adaptation Costs for Urban Drainage Systems

    EPA Science Inventory

    Changes in precipitation patterns associated with climate change may pose significant challenges for storm water management systems across much of the U.S. In particular, adapting these systems to more intense rainfall events will require significant investment. The assessment ...

  4. Model Structure Determination and Identifiability Problems in System Identification.

    DTIC Science & Technology

    System identification has become one of the most active areas in system theory and its applications. In many engineering applications where the...estimation. As the authors extend the concept of system identification to those classes of problems where prior knowledge on structure is limited, some...basic problems other than parameter estimation become important. System identification consists of three basic sub-problems: (1) pre-estimation

  5. Autonomous Frequency-Domain System-Identification Program

    NASA Technical Reports Server (NTRS)

    Yam, Yeung; Mettler, Edward; Bayard, David S.; Hadaegh, Fred Y.; Milman, Mark H.; Scheid, Robert E.

    1993-01-01

    Autonomous Frequency Domain Identification (AU-FREDI) computer program implements system of methods, algorithms, and software developed for identification of parameters of mathematical models of dynamics of flexible structures and characterization, by use of system transfer functions, of such models, dynamics, and structures regarded as systems. Software considered collection of routines modified and reassembled to suit system-identification and control experiments on large flexible structures.

  6. Adaptive model reduction for continuous systems via recursive rational interpolation

    NASA Technical Reports Server (NTRS)

    Lilly, John H.

    1994-01-01

    A method for adaptive identification of reduced-order models for continuous stable SISO and MIMO plants is presented. The method recursively finds a model whose transfer function (matrix) matches that of the plant on a set of frequencies chosen by the designer. The algorithm utilizes the Moving Discrete Fourier Transform (MDFT) to continuously monitor the frequency-domain profile of the system input and output signals. The MDFT is an efficient method of monitoring discrete points in the frequency domain of an evolving function of time. The model parameters are estimated from MDFT data using standard recursive parameter estimation techniques. The algorithm has been shown in simulations to be quite robust to additive noise in the inputs and outputs. A significant advantage of the method is that it enables a type of on-line model validation. This is accomplished by simultaneously identifying a number of models and comparing each with the plant in the frequency domain. Simulations of the method applied to an 8th-order SISO plant and a 10-state 2-input 2-output plant are presented. An example of on-line model validation applied to the SISO plant is also presented.

  7. Multi-Output System Identification Using Evolutionary Programming

    DTIC Science & Technology

    1991-11-04

    Evolutionary programming (EP) has been demonstrated to be an effective method of system identification of single-input-single-output (SISO) systems...This paper investigates the use of EP in system identification of single-input-multioutput (SIMO) systems. EP is used to identify parameters of a

  8. Recursive architecture for large-scale adaptive system

    NASA Astrophysics Data System (ADS)

    Hanahara, Kazuyuki; Sugiyama, Yoshihiko

    1994-09-01

    'Large scale' is one of major trends in the research and development of recent engineering, especially in the field of aerospace structural system. This term expresses the large scale of an artifact in general, however, it also implies the large number of the components which make up the artifact in usual. Considering a large scale system which is especially used in remote space or deep-sea, such a system should be adaptive as well as robust by itself, because its control as well as maintenance by human operators are not easy due to the remoteness. An approach to realizing this large scale, adaptive and robust system is to build the system as an assemblage of components which are respectively adaptive by themselves. In this case, the robustness of the system can be achieved by using a large number of such components and suitable adaptation as well as maintenance strategies. Such a system gathers many research's interest and their studies such as decentralized motion control, configurating algorithm and characteristics of structural elements are reported. In this article, a recursive architecture concept is developed and discussed towards the realization of large scale system which consists of a number of uniform adaptive components. We propose an adaptation strategy based on the architecture and its implementation by means of hierarchically connected processing units. The robustness and the restoration from degeneration of the processing unit are also discussed. Two- and three-dimensional adaptive truss structures are conceptually designed based on the recursive architecture.

  9. Nonlinear model identification and adaptive model predictive control using neural networks.

    PubMed

    Akpan, Vincent A; Hassapis, George D

    2011-04-01

    This paper presents two new adaptive model predictive control algorithms, both consisting of an on-line process identification part and a predictive control part. Both parts are executed at each sampling instant. The predictive control part of the first algorithm is the Nonlinear Model Predictive Control strategy and the control part of the second algorithm is the Generalized Predictive Control strategy. In the identification parts of both algorithms the process model is approximated by a series-parallel neural network structure which is trained by a recursive least squares (ARLS) method. The two control algorithms have been applied to: 1) the temperature control of a fluidized bed furnace reactor (FBFR) of a pilot plant and 2) the auto-pilot control of an F-16 aircraft. The training and validation data of the neural network are obtained from the open-loop simulation of the FBFR and the nonlinear F-16 aircraft models. The identification and control simulation results show that the first algorithm outperforms the second one at the expense of extra computation time.

  10. Systems and Methods for Derivative-Free Adaptive Control

    NASA Technical Reports Server (NTRS)

    Yucelen, Tansel (Inventor); Kim, Kilsoo (Inventor); Calise, Anthony J. (Inventor)

    2015-01-01

    An adaptive control system is disclosed. The control system can control uncertain dynamic systems. The control system can employ one or more derivative-free adaptive control architectures. The control system can further employ one or more derivative-free weight update laws. The derivative-free weight update laws can comprise a time-varying estimate of an ideal vector of weights. The control system of the present invention can therefore quickly stabilize systems that undergo sudden changes in dynamics, caused by, for example, sudden changes in weight. Embodiments of the present invention can also provide a less complex control system than existing adaptive control systems. The control system can control aircraft and other dynamic systems, such as, for example, those with non-minimum phase dynamics.

  11. Adaptive Learning Systems: Beyond Teaching Machines

    ERIC Educational Resources Information Center

    Kara, Nuri; Sevim, Nese

    2013-01-01

    Since 1950s, teaching machines have changed a lot. Today, we have different ideas about how people learn, what instructor should do to help students during their learning process. We have adaptive learning technologies that can create much more student oriented learning environments. The purpose of this article is to present these changes and its…

  12. Hormesis and adaptive cellular control systems

    EPA Science Inventory

    Hormetic dose response occurs for many endpoints associated with exposures of biological organisms to environmental stressors. Cell-based U- or inverted U-shaped responses may derive from common processes involved in activation of adaptive responses required to protect cells from...

  13. A Guide to Computer Adaptive Testing Systems

    ERIC Educational Resources Information Center

    Davey, Tim

    2011-01-01

    Some brand names are used generically to describe an entire class of products that perform the same function. "Kleenex," "Xerox," "Thermos," and "Band-Aid" are good examples. The term "computerized adaptive testing" (CAT) is similar in that it is often applied uniformly across a diverse family of testing methods. Although the various members of…

  14. Adaptive lesion formation using dual mode ultrasound array system

    NASA Astrophysics Data System (ADS)

    Liu, Dalong; Casper, Andrew; Haritonova, Alyona; Ebbini, Emad S.

    2017-03-01

    We present the results from an ultrasound-guided focused ultrasound platform designed to perform real-time monitoring and control of lesion formation. Real-time signal processing of echogenicity changes during lesion formation allows for identification of signature events indicative of tissue damage. The detection of these events triggers the cessation or the reduction of the exposure (intensity and/or time) to prevent overexposure. A dual mode ultrasound array (DMUA) is used for forming single- and multiple-focus patterns in a variety of tissues. The DMUA approach allows for inherent registration between the therapeutic and imaging coordinate systems providing instantaneous, spatially-accurate feedback on lesion formation dynamics. The beamformed RF data has been shown to have high sensitivity and specificity to tissue changes during lesion formation, including in vivo. In particular, the beamformed echo data from the DMUA is very sensitive to cavitation activity in response to HIFU in a variety of modes, e.g. boiling cavitation. This form of feedback is characterized by sudden increase in echogenicity that could occur within milliseconds of the application of HIFU (see http://youtu.be/No2wh-ceTLs for an example). The real-time beamforming and signal processing allowing the adaptive control of lesion formation is enabled by a high performance GPU platform (response time within 10 msec). We present results from a series of experiments in bovine cardiac tissue demonstrating the robustness and increased speed of volumetric lesion formation for a range of clinically-relevant exposures. Gross histology demonstrate clearly that adaptive lesion formation results in tissue damage consistent with the size of the focal spot and the raster scan in 3 dimensions. In contrast, uncontrolled volumetric lesions exhibit significant pre-focal buildup due to excessive exposure from multiple full-exposure HIFU shots. Stopping or reducing the HIFU exposure upon the detection of such an

  15. System Identification of a Vortex Lattice Aerodynamic Model

    NASA Technical Reports Server (NTRS)

    Juang, Jer-Nan; Kholodar, Denis; Dowell, Earl H.

    2001-01-01

    The state-space presentation of an aerodynamic vortex model is considered from a classical and system identification perspective. Using an aerodynamic vortex model as a numerical simulator of a wing tunnel experiment, both full state and limited state data or measurements are considered. Two possible approaches for system identification are presented and modal controllability and observability are also considered. The theory then is applied to the system identification of a flow over an aerodynamic delta wing and typical results are presented.

  16. The Development and Evaluation of a Computerized Adaptive Testing System.

    ERIC Educational Resources Information Center

    de-la-Torre, Roberto; Vispoel, Walter P.

    The development and preliminary evaluation of the Computerized Adaptive Testing System (CATSYS), a new testing package for IBM-compatible microcomputers, are described. CATSYS can be used to administer and score operational adaptive tests or to conduct on-line computer simulation studies. The package incorporates several innovative features,…

  17. [Adaptation potential of cardio-respiratory system in dust diseases].

    PubMed

    Serebryakov, P V; Nenenko, O I; Fedina, I N; Rakhimzyanov, A R

    2016-01-01

    The article covers results of cardio-respiratory system evaluation in workers exposed to dust, on basis of adaptation potential evaluation via calculation of functional changes index and 6 minutes' walk test with continuous assessment of blood oxygenation and heart rate. Adaptation disorders are supported by results of external respiration assessment and echo-cardiography.

  18. Adaptive management of social-ecological systems: the path forward

    USGS Publications Warehouse

    Allen, Craig R.

    2015-01-01

    Adaptive management remains at the forefront of environmental management nearly 40 years after its original conception, largely because we have yet to develop other methodologies that offer the same promise. Despite the criticisms of adaptive management and the numerous failed attempts to implement it, adaptive management has yet to be replaced with a better alternative. The concept persists because it is simple, allows action despite uncertainty, and fosters learning. Moving forward, adaptive management of social-ecological systems provides policymakers, managers and scientists a powerful tool for managing for resilience in the face of uncertainty.

  19. Model reference adaptive control in fractional order systems using discrete-time approximation methods

    NASA Astrophysics Data System (ADS)

    Abedini, Mohammad; Nojoumian, Mohammad Ali; Salarieh, Hassan; Meghdari, Ali

    2015-08-01

    In this paper, model reference control of a fractional order system has been discussed. In order to control the fractional order plant, discrete-time approximation methods have been applied. Plant and reference model are discretized by Grünwald-Letnikov definition of the fractional order derivative using "Short Memory Principle". Unknown parameters of the fractional order system are appeared in the discrete time approximate model as combinations of parameters of the main system. The discrete time MRAC via RLS identification is modified to estimate the parameters and control the fractional order plant. Numerical results show the effectiveness of the proposed method of model reference adaptive control.

  20. Cyberspace: The Ultimate Complex Adaptive System

    DTIC Science & Technology

    2010-04-09

    a transaction with a given agent; tags also facilitate the formation of aggregates , or meta-agents. Meta-agents help distrib- ute and decentralize...Cyber Environments Attribute Physical Environment Cyber Environment Location Latitude, Longitude IP-Address Speed Air and ground in mph Mbps or Gbps...or more capable in terms of its requisite variety (in can adapt to a wider range of conditions). The fitness of the agent is a complex aggregate

  1. Adaptive Control of Nonlinear Flexible Systems

    DTIC Science & Technology

    1993-01-18

    disturbances. The following example illustrates the need for a robust state-feedback law and the sensi- tivity of the exact - linearization based control law... exact linearization , one can bring an input-output approach to a particular case of certainty- equivalence based adaptive control design. We now...are available for this model, exact linearization can be performed. Let C(s) be the compensator that is being used so far in the previous three

  2. Fractional System Identification: An Approach Using Continuous Order-Distributions

    NASA Technical Reports Server (NTRS)

    Hartley, Tom T.; Lorenzo, Carl F.

    1999-01-01

    This paper discusses the identification of fractional- and integer-order systems using the concept of continuous order-distribution. Based on the ability to define systems using continuous order-distributions, it is shown that frequency domain system identification can be performed using least squares techniques after discretizing the order-distribution.

  3. Probing Signal Design for Power System Identification

    SciTech Connect

    Pierre, John W.; Zhou, Ning; Tuffner, Francis K.; Hauer, John F.; Trudnowski, Daniel J.; Mittelstadt, William

    2010-05-31

    This paper investigates the design of effective input signals for low-level probing of power systems. In 2005, 2006, and 2008 the Western Electricity Coordinating Council (WECC) conducted four large-scale system wide tests of the western interconnected power system where probing signals were injected by modulating the control signal at the Celilo end of the Pacific DC intertie. A major objective of these tests is the accurate estimation of the inter-area electromechanical modes. A key aspect of any such test is the design of an effective probing signal that leads to measured outputs rich in information about the modes. This paper specifically studies low-level probing signal design for power-system identification. The paper describes the design methodology and the advantages of this new probing signal which was successfully applied during these tests. This probing input is a multi-sine signal with its frequency content focused in the range of the inter-area modes. The period of the signal is over two minutes providing high-frequency resolution. Up to 15 cycles of the signal are injected resulting in a processing gain of 15. The resulting system response is studied in the time and frequency domains. Because of the new probing signal characteristics, these results show significant improvement in the output SNR compared to previous tests.

  4. Chronic infection and the origin of adaptive immune system.

    PubMed

    Usharauli, David

    2010-08-01

    It has been speculated that the rise of the adaptive immune system in jawed vertebrates some 400 million years ago gave them a superior protection to detect and defend against pathogens that became more elusive and/or virulent to the host that had only innate immune system. First, this line of thought implies that adaptive immune system was a new, more sophisticated layer of host defense that operated independently of the innate immune system. Second, the natural consequence of this scenario would be that pathogens would have exercised so strong an evolutionary pressure that eventually no host could have afforded not to have an adaptive immune system. Neither of these arguments is supported by the facts. First, new experimental evidence has firmly established that operation of adaptive immune system is critically dependent on the ability of the innate immune system to detect invader-pathogens and second, the absolute majority of animal kingdom survives just fine with only an innate immune system. Thus, these data raise the dilemma: If innate immune system was sufficient to detect and protect against pathogens, why then did adaptive immune system develop in the first place? In contrast to the innate immune system, the adaptive immune system has one important advantage, precision. By precision I mean the ability of the defense system to detect and remove the target, for example, infected cells, without causing unwanted bystander damage of surrounding tissue. While the target precision per se is not important for short-term immune response, it becomes a critical factor when the immune response is long-lasting, as during chronic infection. In this paper I would like to propose new, "toxic index" hypothesis where I argue that the need to reduce the collateral damage to the tissue during chronic infection(s) was the evolutionary pressure that led to the development of the adaptive immune system.

  5. Advanced Techniques for Power System Identification from Measured Data

    SciTech Connect

    Pierre, John W.; Wies, Richard; Trudnowski, Daniel

    2008-11-25

    Time-synchronized measurements provide rich information for estimating a power-system's electromechanical modal properties via advanced signal processing. This information is becoming critical for the improved operational reliability of interconnected grids. A given mode's properties are described by its frequency, damping, and shape. Modal frequencies and damping are useful indicators of power-system stress, usually declining with increased load or reduced grid capacity. Mode shape provides critical information for operational control actions. This project investigated many advanced techniques for power system identification from measured data focusing on mode frequency and damping ratio estimation. Investigators from the three universities coordinated their effort with Pacific Northwest National Laboratory (PNNL). Significant progress was made on developing appropriate techniques for system identification with confidence intervals and testing those techniques on field measured data and through simulation. Experimental data from the western area power system was provided by PNNL and Bonneville Power Administration (BPA) for both ambient conditions and for signal injection tests. Three large-scale tests were conducted for the western area in 2005 and 2006. Measured field PMU (Phasor Measurement Unit) data was provided to the three universities. A 19-machine simulation model was enhanced for testing the system identification algorithms. Extensive simulations were run with this model to test the performance of the algorithms. University of Wyoming researchers participated in four primary activities: (1) Block and adaptive processing techniques for mode estimation from ambient signals and probing signals, (2) confidence interval estimation, (3) probing signal design and injection method analysis, and (4) performance assessment and validation from simulated and field measured data. Subspace based methods have been use to improve previous results from block processing

  6. System identification of physiological systems using short data segments.

    PubMed

    Ludvig, Daniel; Perreault, Eric J

    2012-12-01

    System identification of physiological systems poses unique challenges, especially when the structure of the system under study is uncertain. Nonparametric techniques can be useful for identifying system structure, but these typically assume stationarity and require large amounts of data. Both of these requirements are often not easily obtained in the study of physiological systems. Ensemble methods for time-varying nonparametric estimation have been developed to address the issue of stationarity, but these require an amount of data that can be prohibitive for many experimental systems. To address this issue, we developed a novel algorithm that uses multiple short data segments. Using simulation studies, we showed that this algorithm produces system estimates with lower variability than previous methods when limited data are present. Furthermore, we showed that the new algorithm generates time-varying system estimates with lower total error than an ensemble method. Thus, this algorithm is well suited for the identification of physiological systems that vary with time or from which only short segments of stationary data can be collected.

  7. System Identification of Physiological Systems Using Short Data Segments

    PubMed Central

    Perreault, Eric J.

    2013-01-01

    System identification of physiological systems poses unique challenges, especially when the structure of the system under study is uncertain. Non-parametric techniques can be useful for identifying system structure, but these typically assume stationarity, and require large amounts of data. Both of these requirements are often not easily obtained in the study of physiological systems. Ensemble methods for time-varying, non-parametric estimation have been developed to address the issue of stationarity, but these require an amount of data that can be prohibitive for many experimental systems. To address this issue, we developed a novel algorithm that uses multiple short data segments. Using simulation studies, we showed that this algorithm produces system estimates with lower variability than previous methods when limited data are present. Furthermore we showed that the new algorithm generates time-varying system estimates with lower total error than an ensemble method. Thus, this algorithm is well suited for the identification of physiological systems that vary with time or from which only short segments of stationary data can be collected. PMID:23033429

  8. Cultural adaptation, content validity and inter-rater reliability of the "STAR Skin Tear Classification System"1

    PubMed Central

    Strazzieri-Pulido, Kelly Cristina; Santos, Vera Lúcia Conceição de Gouveia; Carville, Keryln

    2015-01-01

    AIMS: to perform the cultural adaptation of the STAR Skin Tear Classification System into the Portuguese language and to test the content validity and inter-rater reliability of the adapted version. METHODS: methodological study with a quantitative approach. The cultural adaptation was developed in three phases: translation, evaluation by a committee of judges and back-translation. The instrument was tested regarding content validity and inter-rater reliability. RESULTS: the adapted version obtained a regular level of concordance when it was applied by nurses using photographs of friction injuries. Regarding its application in clinical practice, the adapted version obtained a moderate and statistically significant level of concordance. CONCLUSION: the study tested the content validity and inter-rater reliability of the version adapted into the Portuguese language. Its inclusion in clinical practice will enable the correct identification of this type of injury, as well as the implementation of protocols for the prevention and treatment of friction injuries. PMID:25806644

  9. Thermal Signature Identification System (TheSIS)

    NASA Technical Reports Server (NTRS)

    Merritt, Scott; Bean, Brian

    2015-01-01

    We characterize both nonlinear and high order linear responses of fiber-optic and optoelectronic components using spread spectrum temperature cycling methods. This Thermal Signature Identification System (TheSIS) provides much more detail than conventional narrowband or quasi-static temperature profiling methods. This detail allows us to match components more thoroughly, detect subtle reversible shifts in performance, and investigate the cause of instabilities or irreversible changes. In particular, we create parameterized models of athermal fiber Bragg gratings (FBGs), delay line interferometers (DLIs), and distributed feedback (DFB) lasers, then subject the alternative models to selection via the Akaike Information Criterion (AIC). Detailed pairing of components, e.g. FBGs, is accomplished by means of weighted distance metrics or norms, rather than on the basis of a single parameter, such as center wavelength.

  10. RASCAL: A Rudimentary Adaptive System for Computer-Aided Learning.

    ERIC Educational Resources Information Center

    Stewart, John Christopher

    Both the background of computer-assisted instruction (CAI) systems in general and the requirements of a computer-aided learning system which would be a reasonable assistant to a teacher are discussed. RASCAL (Rudimentary Adaptive System for Computer-Aided Learning) is a first attempt at defining a CAI system which would individualize the learning…

  11. Advanced driver assistance system: Road sign identification using VIAPIX system and a correlation technique

    NASA Astrophysics Data System (ADS)

    Ouerhani, Y.; Alfalou, A.; Desthieux, M.; Brosseau, C.

    2017-02-01

    We present a three-step approach based on the commercial VIAPIX® module for road traffic sign recognition and identification. Firstly, detection in a scene of all objects having characteristics of traffic signs is performed. This is followed by a first-level recognition based on correlation which consists in making a comparison between each detected object with a set of reference images of a database. Finally, a second level of identification allows us to confirm or correct the previous identification. In this study, we perform a correlation-based analysis by combining and adapting the Vander Lugt correlator with the nonlinear joint transformation correlator (JTC). Of particular significance, this approach permits to make a reliable decision on road traffic sign identification. We further discuss a robust scheme allowing us to track a detected road traffic sign in a video sequence for the purpose of increasing the decision performance of our system. This approach can have broad practical applications in the maintenance and rehabilitation of transportation infrastructure, or for drive assistance.

  12. An overview of recent advances in system identification

    NASA Astrophysics Data System (ADS)

    Juang, Jer-Nan

    1994-06-01

    This paper presents an overview of the recent advances in system identification for modal testing and control of large flexible structures. Several techniques are discussed including the Observer/Kalman Filter Identification, the Observer/Controller Identification, and the State-Space System Identification in the Frequency Domain. The System/Observer/Controller Toolbox developed at NASA Langley Research Center is used to show the applications of these techniques to real aerospace structures such as the Hubble spacecraft telescope and the active flexible aircraft wing.

  13. An overview of recent advances in system identification

    NASA Technical Reports Server (NTRS)

    Juang, Jer-Nan

    1994-01-01

    This paper presents an overview of the recent advances in system identification for modal testing and control of large flexible structures. Several techniques are discussed including the Observer/Kalman Filter Identification, the Observer/Controller Identification, and the State-Space System Identification in the Frequency Domain. The System/Observer/Controller Toolbox developed at NASA Langley Research Center is used to show the applications of these techniques to real aerospace structures such as the Hubble spacecraft telescope and the active flexible aircraft wing.

  14. Identification of the Unstable Human Postural Control System.

    PubMed

    Hwang, Sungjae; Agada, Peter; Kiemel, Tim; Jeka, John J

    2016-01-01

    Maintaining upright bipedal posture requires a control system that continually adapts to changing environmental conditions, such as different support surfaces. Behavioral changes associated with different support surfaces, such as the predominance of an ankle or hip strategy, is considered to reflect a change in the control strategy. However, tracing such behavioral changes to a specific component in a closed loop control system is challenging. Here we used the joint input-output (JIO) method of closed-loop system identification to identify the musculoskeletal and neural feedback components of the human postural control loop. The goal was to establish changes in the control loop corresponding to behavioral changes observed on different support surfaces. Subjects were simultaneously perturbed by two independent mechanical and two independent sensory perturbations while standing on a normal or short support surface. The results show a dramatic phase reversal between visual input and body kinematics due to the change in surface condition from trunk leads legs to legs lead trunk with increasing frequency of the visual perturbation. Through decomposition of the control loop, we found that behavioral change is not necessarily due to a change in control strategy, but in the case of different support surfaces, is linked to changes in properties of the plant. The JIO method is an important tool to identify the contribution of specific components within a closed loop control system to overall postural behavior and may be useful to devise better treatment of balance disorders.

  15. Design of a digital adaptive control system for reentry vehicles.

    NASA Technical Reports Server (NTRS)

    Picon-Jimenez, J. L.; Montgomery, R. C.; Grigsby, L. L.

    1972-01-01

    The flying qualities of atmospheric reentry vehicles experience considerable variations due to the wide changes in flight conditions characteristic of reentry trajectories. A digital adaptive control system has been designed to modify the vehicle's dynamic characteristics and to provide desired flying qualities for all flight conditions. This adaptive control system consists of a finite-memory identifier which determines the vehicle's unknown parameters, and a gain computer which calculates feedback gains to satisfy flying quality requirements.

  16. Global adaptive control for uncertain nonaffine nonlinear hysteretic systems.

    PubMed

    Liu, Yong-Hua; Huang, Liangpei; Xiao, Dongming; Guo, Yong

    2015-09-01

    In this paper, the global output tracking is investigated for a class of uncertain nonlinear hysteretic systems with nonaffine structures. By combining the solution properties of the hysteresis model with the novel backstepping approach, a robust adaptive control algorithm is developed without constructing a hysteresis inverse. The proposed control scheme is further modified to tackle the bounded disturbances by adaptively estimating their bounds. It is rigorously proven that the designed adaptive controllers can guarantee global stability of the closed-loop system. Two numerical examples are provided to show the effectiveness of the proposed control schemes.

  17. Clustering of tethered satellite system simulation data by an adaptive neuro-fuzzy algorithm

    NASA Technical Reports Server (NTRS)

    Mitra, Sunanda; Pemmaraju, Surya

    1992-01-01

    Recent developments in neuro-fuzzy systems indicate that the concepts of adaptive pattern recognition, when used to identify appropriate control actions corresponding to clusters of patterns representing system states in dynamic nonlinear control systems, may result in innovative designs. A modular, unsupervised neural network architecture, in which fuzzy learning rules have been embedded is used for on-line identification of similar states. The architecture and control rules involved in Adaptive Fuzzy Leader Clustering (AFLC) allow this system to be incorporated in control systems for identification of system states corresponding to specific control actions. We have used this algorithm to cluster the simulation data of Tethered Satellite System (TSS) to estimate the range of delta voltages necessary to maintain the desired length rate of the tether. The AFLC algorithm is capable of on-line estimation of the appropriate control voltages from the corresponding length error and length rate error without a priori knowledge of their membership functions and familarity with the behavior of the Tethered Satellite System.

  18. Adaptive Mesh Refinement and Adaptive Time Integration for Electrical Wave Propagation on the Purkinje System.

    PubMed

    Ying, Wenjun; Henriquez, Craig S

    2015-01-01

    A both space and time adaptive algorithm is presented for simulating electrical wave propagation in the Purkinje system of the heart. The equations governing the distribution of electric potential over the system are solved in time with the method of lines. At each timestep, by an operator splitting technique, the space-dependent but linear diffusion part and the nonlinear but space-independent reactions part in the partial differential equations are integrated separately with implicit schemes, which have better stability and allow larger timesteps than explicit ones. The linear diffusion equation on each edge of the system is spatially discretized with the continuous piecewise linear finite element method. The adaptive algorithm can automatically recognize when and where the electrical wave starts to leave or enter the computational domain due to external current/voltage stimulation, self-excitation, or local change of membrane properties. Numerical examples demonstrating efficiency and accuracy of the adaptive algorithm are presented.

  19. Adaptive Mesh Refinement and Adaptive Time Integration for Electrical Wave Propagation on the Purkinje System

    PubMed Central

    Ying, Wenjun; Henriquez, Craig S.

    2015-01-01

    A both space and time adaptive algorithm is presented for simulating electrical wave propagation in the Purkinje system of the heart. The equations governing the distribution of electric potential over the system are solved in time with the method of lines. At each timestep, by an operator splitting technique, the space-dependent but linear diffusion part and the nonlinear but space-independent reactions part in the partial differential equations are integrated separately with implicit schemes, which have better stability and allow larger timesteps than explicit ones. The linear diffusion equation on each edge of the system is spatially discretized with the continuous piecewise linear finite element method. The adaptive algorithm can automatically recognize when and where the electrical wave starts to leave or enter the computational domain due to external current/voltage stimulation, self-excitation, or local change of membrane properties. Numerical examples demonstrating efficiency and accuracy of the adaptive algorithm are presented. PMID:26581455

  20. Lightweight autonomous chemical identification system (LACIS)

    NASA Astrophysics Data System (ADS)

    Lozos, George; Lin, Hai; Burch, Timothy

    2012-06-01

    Smiths Detection and Intelligent Optical Systems have developed prototypes for the Lightweight Autonomous Chemical Identification System (LACIS) for the US Department of Homeland Security. LACIS is to be a handheld detection system for Chemical Warfare Agents (CWAs) and Toxic Industrial Chemicals (TICs). LACIS is designed to have a low limit of detection and rapid response time for use by emergency responders and could allow determination of areas having dangerous concentration levels and if protective garments will be required. Procedures for protection of responders from hazardous materials incidents require the use of protective equipment until such time as the hazard can be assessed. Such accurate analysis can accelerate operations and increase effectiveness. LACIS is to be an improved point detector employing novel CBRNE detection modalities that includes a militaryproven ruggedized ion mobility spectrometer (IMS) with an array of electro-resistive sensors to extend the range of chemical threats detected in a single device. It uses a novel sensor data fusion and threat classification architecture to interpret the independent sensor responses and provide robust detection at low levels in complex backgrounds with minimal false alarms. The performance of LACIS prototypes have been characterized in independent third party laboratory tests at the Battelle Memorial Institute (BMI, Columbus, OH) and indoor and outdoor field tests at the Nevada National Security Site (NNSS). LACIS prototypes will be entering operational assessment by key government emergency response groups to determine its capabilities versus requirements.

  1. Optimizing Input/Output Using Adaptive File System Policies

    NASA Technical Reports Server (NTRS)

    Madhyastha, Tara M.; Elford, Christopher L.; Reed, Daniel A.

    1996-01-01

    Parallel input/output characterization studies and experiments with flexible resource management algorithms indicate that adaptivity is crucial to file system performance. In this paper we propose an automatic technique for selecting and refining file system policies based on application access patterns and execution environment. An automatic classification framework allows the file system to select appropriate caching and pre-fetching policies, while performance sensors provide feedback used to tune policy parameters for specific system environments. To illustrate the potential performance improvements possible using adaptive file system policies, we present results from experiments involving classification-based and performance-based steering.

  2. Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

    PubMed

    Villaverde, Monica; Perez, David; Moreno, Felix

    2015-11-17

    The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

  3. Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors

    PubMed Central

    Villaverde, Monica; Perez, David; Moreno, Felix

    2015-01-01

    The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc. PMID:26593920

  4. Detection of Anthropogenic Particles in Fish Stomachs: An Isolation Method Adapted to Identification by Raman Spectroscopy.

    PubMed

    Collard, France; Gilbert, Bernard; Eppe, Gauthier; Parmentier, Eric; Das, Krishna

    2015-10-01

    Microplastic particles (MP) contaminate oceans and affect marine organisms in several ways. Ingestion combined with food intake is generally reported. However, data interpretation often is circumvented by the difficulty to separate MP from bulk samples. Visual examination often is used as one or the only step to sort these particles. However, color, size, and shape are insufficient and often unreliable criteria. We present an extraction method based on hypochlorite digestion and isolation of MP from the membrane by sonication. The protocol is especially well adapted to a subsequent analysis by Raman spectroscopy. The method avoids fluorescence problems, allowing better identification of anthropogenic particles (AP) from stomach contents of fish by Raman spectroscopy. It was developed with commercial samples of microplastics and cotton along with stomach contents from three different Clupeiformes fishes: Clupea harengus, Sardina pilchardus, and Engraulis encrasicolus. The optimized digestion and isolation protocol showed no visible impact on microplastics and cotton particles while the Raman spectroscopic spectrum allowed the precise identification of microplastics and textile fibers. Thirty-five particles were isolated from nine fish stomach contents. Raman analysis has confirmed 11 microplastics and 13 fibers mainly made of cellulose or lignin. Some particles were not completely identified but contained artificial dyes. The novel approach developed in this manuscript should help to assess the presence, quantity, and composition of AP in planktivorous fish stomachs.

  5. Adaptive integral robust control and application to electromechanical servo systems.

    PubMed

    Deng, Wenxiang; Yao, Jianyong

    2017-03-01

    This paper proposes a continuous adaptive integral robust control with robust integral of the sign of the error (RISE) feedback for a class of uncertain nonlinear systems, in which the RISE feedback gain is adapted online to ensure the robustness against disturbances without the prior bound knowledge of the additive disturbances. In addition, an adaptive compensation integrated with the proposed adaptive RISE feedback term is also constructed to further reduce design conservatism when the system also exists parametric uncertainties. Lyapunov analysis reveals the proposed controllers could guarantee the tracking errors are asymptotically converging to zero with continuous control efforts. To illustrate the high performance nature of the developed controllers, numerical simulations are provided. At the end, an application case of an actual electromechanical servo system driven by motor is also studied, with some specific design consideration, and comparative experimental results are obtained to verify the effectiveness of the proposed controllers.

  6. Identification of SPAM messages using an approach inspired on the immune system.

    PubMed

    Guzella, T S; Mota-Santos, T A; Uchôa, J Q; Caminhas, W M

    2008-06-01

    In this paper, an immune-inspired model, named innate and adaptive artificial immune system (IA-AIS) is proposed and applied to the problem of identification of unsolicited bulk e-mail messages (SPAM). It integrates entities analogous to macrophages, B and T lymphocytes, modeling both the innate and the adaptive immune systems. An implementation of the algorithm was capable of identifying more than 99% of legitimate or SPAM messages in particular parameter configurations. It was compared to an optimized version of the naive Bayes classifier, which has been attained extremely high correct classification rates. It has been concluded that IA-AIS has a greater ability to identify SPAM messages, although the identification of legitimate messages is not as high as that of the implemented naive Bayes classifier.

  7. Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.

    PubMed

    Zhang, Yanjun; Tao, Gang; Chen, Mou

    2016-09-01

    This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method.

  8. Evaluation of Fungichrom 1: a new yeast identification system.

    PubMed

    Umabala, P; Satheeshkumar, T; Lakshmi, V

    2002-01-01

    Advances in anti-fungal therapy necessitate the need for accurate identification of fungi especially yeasts to their species level for more effective management. Unlike the time consuming conventional methods of yeast identification using fermentation and assimilation patterns of various carbohydrates, the new commercialized yeast identification systems are simpler, rapid and are particularly easy to interpret. In our study, a new colorimetric yeast identification system-Fungichrom 1(International microbio, Signes, France) was evaluated against the conventional method to identify 50 clinical isolates of yeasts belonging to the genera -Candida, Cryptococcus, Geotrichum. 96% agreement was found between the two methods.

  9. Optimized Treatment of Fibromyalgia Using System Identification and Hybrid Model Predictive Control

    PubMed Central

    Deshpande, Sunil; Nandola, Naresh N.; Rivera, Daniel E.; Younger, Jarred W.

    2014-01-01

    The term adaptive intervention is used in behavioral health to describe individually-tailored strategies for preventing and treating chronic, relapsing disorders. This paper describes a system identification approach for developing dynamical models from clinical data, and subsequently, a hybrid model predictive control scheme for assigning dosages of naltrexone as treatment for fibromyalgia, a chronic pain condition. A simulation study that includes conditions of significant plant-model mismatch demonstrates the benefits of hybrid predictive control as a decision framework for optimized adaptive interventions. This work provides insights on the design of novel personalized interventions for chronic pain and related conditions in behavioral health. PMID:25506132

  10. Optimized Treatment of Fibromyalgia Using System Identification and Hybrid Model Predictive Control.

    PubMed

    Deshpande, Sunil; Nandola, Naresh N; Rivera, Daniel E; Younger, Jarred W

    2014-12-01

    The term adaptive intervention is used in behavioral health to describe individually-tailored strategies for preventing and treating chronic, relapsing disorders. This paper describes a system identification approach for developing dynamical models from clinical data, and subsequently, a hybrid model predictive control scheme for assigning dosages of naltrexone as treatment for fibromyalgia, a chronic pain condition. A simulation study that includes conditions of significant plant-model mismatch demonstrates the benefits of hybrid predictive control as a decision framework for optimized adaptive interventions. This work provides insights on the design of novel personalized interventions for chronic pain and related conditions in behavioral health.

  11. System identification and model reduction using modulating function techniques

    NASA Technical Reports Server (NTRS)

    Shen, Yan

    1993-01-01

    Weighted least squares (WLS) and adaptive weighted least squares (AWLS) algorithms are initiated for continuous-time system identification using Fourier type modulating function techniques. Two stochastic signal models are examined using the mean square properties of the stochastic calculus: an equation error signal model with white noise residuals, and a more realistic white measurement noise signal model. The covariance matrices in each model are shown to be banded and sparse, and a joint likelihood cost function is developed which links the real and imaginary parts of the modulated quantities. The superior performance of above algorithms is demonstrated by comparing them with the LS/MFT and popular predicting error method (PEM) through 200 Monte Carlo simulations. A model reduction problem is formulated with the AWLS/MFT algorithm, and comparisons are made via six examples with a variety of model reduction techniques, including the well-known balanced realization method. Here the AWLS/MFT algorithm manifests higher accuracy in almost all cases, and exhibits its unique flexibility and versatility. Armed with this model reduction, the AWLS/MFT algorithm is extended into MIMO transfer function system identification problems. The impact due to the discrepancy in bandwidths and gains among subsystem is explored through five examples. Finally, as a comprehensive application, the stability derivatives of the longitudinal and lateral dynamics of an F-18 aircraft are identified using physical flight data provided by NASA. A pole-constrained SIMO and MIMO AWLS/MFT algorithm is devised and analyzed. Monte Carlo simulations illustrate its high-noise rejecting properties. Utilizing the flight data, comparisons among different MFT algorithms are tabulated and the AWLS is found to be strongly favored in almost all facets.

  12. Adaptive Fuzzy Systems in Computational Intelligence

    NASA Technical Reports Server (NTRS)

    Berenji, Hamid R.

    1996-01-01

    In recent years, the interest in computational intelligence techniques, which currently includes neural networks, fuzzy systems, and evolutionary programming, has grown significantly and a number of their applications have been developed in the government and industry. In future, an essential element in these systems will be fuzzy systems that can learn from experience by using neural network in refining their performances. The GARIC architecture, introduced earlier, is an example of a fuzzy reinforcement learning system which has been applied in several control domains such as cart-pole balancing, simulation of to Space Shuttle orbital operations, and tether control. A number of examples from GARIC's applications in these domains will be demonstrated.

  13. Model-on-Demand Predictive Control for Nonlinear Hybrid Systems With Application to Adaptive Behavioral Interventions

    PubMed Central

    Nandola, Naresh N.; Rivera, Daniel E.

    2011-01-01

    This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem because model parameters depend on the mode or operating point of the system. The proposed algorithm applies Model-on-Demand (MoD) estimation to generate a local linear approximation of the nonlinear hybrid system at each time step, using a small subset of data selected by an adaptive bandwidth selector. The appeal of the MoD approach lies in the fact that model parameters are estimated based on a current operating point; hence estimation of locations or modes governed by autonomous discrete events is achieved automatically. The local MoD model is then converted into a mixed logical dynamical (MLD) system representation which can be used directly in a model predictive control (MPC) law for hybrid systems using multiple-degree-of-freedom tuning. The effectiveness of the proposed MoD predictive control algorithm for nonlinear hybrid systems is demonstrated on a hypothetical adaptive behavioral intervention problem inspired by Fast Track, a real-life preventive intervention for improving parental function and reducing conduct disorder in at-risk children. Simulation results demonstrate that the proposed algorithm can be useful for adaptive intervention problems exhibiting both nonlinear and hybrid character. PMID:21874087

  14. Adaptive controller for a needle free jet-injector system.

    PubMed

    Modak, Ashin; Hogan, N Catherine; Hunter, Ian W

    2015-01-01

    A nonlinear, sliding mode adaptive controller was created for a needle-free jet injection system. The controller was based on a simplified lumped-sum parameter model of the jet-injection mechanics. The adaptive control scheme was compared to a currently-used Feed-forward+PID controller in both ejection of water into air, and injection of dye into ex-vivo porcine tissue. The adaptive controller was more successful in trajectory tracking and was more robust to the biological variations caused by a tissue load.

  15. State of the art in adaptive control of robotic systems

    NASA Technical Reports Server (NTRS)

    Tosunoglu, Sabri; Tesar, Delbert

    1988-01-01

    An up-to-date assessment of adaptive control technology as applied to robotics is presented. Although the field is relatively new and does not yet represent a mature discipline, considerable attention for the design of sophisticated robot controllers has occured. In this presentation, adaptive control methods are divided into model reference adaptive systems and self-tuning regulators, with further definition of various approaches given in each class. The similarity and distinct features of the designed controllers are delineated and tabulated to enhance comparative review.

  16. Adaptive control of Hammerstein-Wiener nonlinear systems

    NASA Astrophysics Data System (ADS)

    Zhang, Bi; Hong, Hyokchan; Mao, Zhizhong

    2016-07-01

    The Hammerstein-Wiener model is a block-oriented model, having a linear dynamic block sandwiched by two static nonlinear blocks. This note develops an adaptive controller for a special form of Hammerstein-Wiener nonlinear systems which are parameterized by the key-term separation principle. The adaptive control law and recursive parameter estimation are updated by the use of internal variable estimations. By modeling the errors due to the estimation of internal variables, we establish convergence and stability properties. Theoretical results show that parameter estimation convergence and closed-loop system stability can be guaranteed under sufficient condition. From a qualitative analysis of the sufficient condition, we introduce an adaptive weighted factor to improve the performance of the adaptive controller. Numerical examples are given to confirm the results in this paper.

  17. Communication system with adaptive noise suppression

    NASA Technical Reports Server (NTRS)

    Kozel, David (Inventor); Devault, James A. (Inventor); Birr, Richard B. (Inventor)

    2007-01-01

    A signal-to-noise ratio dependent adaptive spectral subtraction process eliminates noise from noise-corrupted speech signals. The process first pre-emphasizes the frequency components of the input sound signal which contain the consonant information in human speech. Next, a signal-to-noise ratio is determined and a spectral subtraction proportion adjusted appropriately. After spectral subtraction, low amplitude signals can be squelched. A single microphone is used to obtain both the noise-corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoiced frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Spectral subtraction may be performed on a composite noise-corrupted signal, or upon individual sub-bands of the noise-corrupted signal. Pre-averaging of the input signal's magnitude spectrum over multiple time frames may be performed to reduce musical noise.

  18. Adaptive Parameter Identification Based on Morlet Wavelet and Application in Gearbox Fault Feature Detection

    NASA Astrophysics Data System (ADS)

    Wang, Shibin; Zhu, Z. K.; He, Yingping; Huang, Weiguo

    2010-12-01

    Localized defects in rotating mechanical parts tend to result in impulse response in vibration signal, which contain important information about system dynamics being analyzed. Thus, parameter identification of impulse response provides a potential approach for localized fault diagnosis. A method combining the Morlet wavelet and correlation filtering, named Cyclic Morlet Wavelet Correlation Filtering (CMWCF), is proposed for identifying both parameters of impulse response and the cyclic period between adjacent impulses. Simulation study concerning cyclic impulse response signal with different SNR shows that CMWCF is effective in identifying the impulse response parameters and the cyclic period. Applications in parameter identification of gearbox vibration signal for localized fault diagnosis show that CMWCF is effective in identifying the parameters and thus provides a feature detection method for gearbox fault diagnosis.

  19. Adaptive sliding mode control for a class of chaotic systems

    NASA Astrophysics Data System (ADS)

    Farid, R.; Ibrahim, A.; Zalam, B.

    2015-03-01

    Chaos control here means to design a controller that is able to mitigating or eliminating the chaos behavior of nonlinear systems that experiencing such phenomenon. In this paper, an Adaptive Sliding Mode Controller (ASMC) is presented based on Lyapunov stability theory. The well known Chua's circuit is chosen to be our case study in this paper. The study shows the effectiveness of the proposed adaptive sliding mode controller.

  20. Adaptive sliding mode control for a class of chaotic systems

    SciTech Connect

    Farid, R.; Ibrahim, A.; Zalam, B.

    2015-03-30

    Chaos control here means to design a controller that is able to mitigating or eliminating the chaos behavior of nonlinear systems that experiencing such phenomenon. In this paper, an Adaptive Sliding Mode Controller (ASMC) is presented based on Lyapunov stability theory. The well known Chua's circuit is chosen to be our case study in this paper. The study shows the effectiveness of the proposed adaptive sliding mode controller.

  1. Distributed adaptive simulation through standards-based integration of simulators and adaptive learning systems.

    PubMed

    Bergeron, Bryan; Cline, Andrew; Shipley, Jaime

    2012-01-01

    We have developed a distributed, standards-based architecture that enables simulation and simulator designers to leverage adaptive learning systems. Our approach, which incorporates an electronic competency record, open source LMS, and open source microcontroller hardware, is a low-cost, pragmatic option to integrating simulators with traditional courseware.

  2. MACAO-VLTI adaptive optics systems performance

    NASA Astrophysics Data System (ADS)

    Arsenault, Robin; Donaldson, Rob; Dupuy, Christophe; Fedrigo, Enrico; Hubin, Norbert N.; Ivanescu, Liviu; Kasper, Markus E.; Oberti, Sylvain; Paufique, Jerome; Rossi, Silvio; Silber, Armin; Delabre, Bernhard; Lizon, Jean-Louis; Gigan, Pierre

    2004-10-01

    In April and August "03 two MACAO-VLTI curvature AO systems were installed on the VLT telescopes unit 2 and 3 in Paranal (Chile). These are 60 element systems using a 150mm bimorph deformable mirror and 60 APD"s as WFS detectors. Valuable integration & commissioning experience has been gained during these 2 missions. Several tests have been performed in order to evaluate system performance on the sky. The systems have proven to be extremely robust, performing in a stable fashion in extreme seeing condition (seeing up to 3"). Strehl ratio of 0.65 and residual tilt smaller than 10 mas have been obtained on the sky in 0.8" seeing condition. Weak guide source performance is also excellent with a strehl of 0.26 on a V~16 magnitude star. Several functionalities have been successfully tested including: chopping, off-axis guiding, atmospheric refraction compensation etc. The AO system can be used in a totally automatic fashion with a small overhead: the AO loop can be closed on the target less than 60 sec after star acquisition by the telescope. It includes reading the seeing value given by the site monitor, evaluate the guide star magnitude (cycling through neutral density filters) setting the close-loop AO parameters (system gain and vibrating membrane mirror stroke) including calculation of the command-matrix. The last 2 systems will be installed in August "04 and in the course of 2005.

  3. Nonlinear system identification based on internal recurrent neural networks.

    PubMed

    Puscasu, Gheorghe; Codres, Bogdan; Stancu, Alexandru; Murariu, Gabriel

    2009-04-01

    A novel approach for nonlinear complex system identification based on internal recurrent neural networks (IRNN) is proposed in this paper. The computational complexity of neural identification can be greatly reduced if the whole system is decomposed into several subsystems. This approach employs internal state estimation when no measurements coming from the sensors are available for the system states. A modified backpropagation algorithm is introduced in order to train the IRNN for nonlinear system identification. The performance of the proposed design approach is proven on a car simulator case study.

  4. Screening systems adapt to changing conditions

    SciTech Connect

    Fiscor, S.

    2009-08-15

    Prep plants are installing larger screening systems and synthetic media is meeting those challenges. The largest manufacturer of synthetic screen media is Polydeck located in Spartanburg, South Carolina. The company's primary product lines include modular polyurethane and rubber screen panels and the frame systems to support the media. The modular approach overcomes a wear problem in one area of the deck common on Banana screens and facilitates maintenance. A rubber formation used in 1- x 2-pt screen panels called the Flexi design is softer and allows more vibration than standard urethane panels. The Maxi screen panel design combined with the PipeTop II frame makes the system highly versatile. 1 photo.

  5. Decentralized system identification using stochastic subspace identification for wireless sensor networks.

    PubMed

    Cho, Soojin; Park, Jong-Woong; Sim, Sung-Han

    2015-04-08

    Wireless sensor networks (WSNs) facilitate a new paradigm to structural identification and monitoring for civil infrastructure. Conventional structural monitoring systems based on wired sensors and centralized data acquisition systems are costly for installation as well as maintenance. WSNs have emerged as a technology that can overcome such difficulties, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing is common practice, WSNs require decentralized computing algorithms to reduce data transmission due to the limitation associated with wireless communication. In this paper, the stochastic subspace identification (SSI) technique is selected for system identification, and SSI-based decentralized system identification (SDSI) is proposed to be implemented in a WSN composed of Imote2 wireless sensors that measure acceleration. The SDSI is tightly scheduled in the hierarchical WSN, and its performance is experimentally verified in a laboratory test using a 5-story shear building model.

  6. An adaptive learning control system for aircraft

    NASA Technical Reports Server (NTRS)

    Mekel, R.; Nachmias, S.

    1978-01-01

    A learning control system and its utilization as a flight control system for F-8 Digital Fly-By-Wire (DFBW) research aircraft is studied. The system has the ability to adjust a gain schedule to account for changing plant characteristics and to improve its performance and the plant's performance in the course of its own operation. Three subsystems are detailed: (1) the information acquisition subsystem which identifies the plant's parameters at a given operating condition; (2) the learning algorithm subsystem which relates the identified parameters to predetermined analytical expressions describing the behavior of the parameters over a range of operating conditions; and (3) the memory and control process subsystem which consists of the collection of updated coefficients (memory) and the derived control laws. Simulation experiments indicate that the learning control system is effective in compensating for parameter variations caused by changes in flight conditions.

  7. Neural system prediction and identification challenge

    PubMed Central

    Vlachos, Ioannis; Zaytsev, Yury V.; Spreizer, Sebastian; Aertsen, Ad; Kumar, Arvind

    2013-01-01

    Can we infer the function of a biological neural network (BNN) if we know the connectivity and activity of all its constituent neurons?This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC). We provide the connectivity and activity of all neurons and invite participants (1) to infer the functions implemented (hard-wired) in spiking neural networks (SNNs) by stimulating and recording the activity of neurons and, (2) to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered. PMID:24399966

  8. UASIS: Universal Automatic SNP Identification System

    PubMed Central

    2011-01-01

    Background SNP (Single Nucleotide Polymorphism), the most common genetic variations between human beings, is believed to be a promising way towards personalized medicine. As more and more research on SNPs are being conducted, non-standard nomenclatures may generate potential problems. The most serious issue is that researchers cannot perform cross referencing among different SNP databases. This will result in more resources and time required to track SNPs. It could be detrimental to the entire academic community. Results UASIS (Universal Automated SNP Identification System) is a web-based server for SNP nomenclature standardization and translation at DNA level. Three utilities are available. They are UASIS Aligner, Universal SNP Name Generator and SNP Name Mapper. UASIS maps SNPs from different databases, including dbSNP, GWAS, HapMap and JSNP etc., into an uniform view efficiently using a proposed universal nomenclature and state-of-art alignment algorithms. UASIS is freely available at http://www.uasis.tk with no requirement of log-in. Conclusions UASIS is a helpful platform for SNP cross referencing and tracking. By providing an informative, unique and unambiguous nomenclature, which utilizes unique position of a SNP, we aim to resolve the ambiguity of SNP nomenclatures currently practised. Our universal nomenclature is a good complement to mainstream SNP notations such as rs# and HGVS guidelines. UASIS acts as a bridge to connect heterogeneous representations of SNPs. PMID:22369494

  9. Neural system prediction and identification challenge.

    PubMed

    Vlachos, Ioannis; Zaytsev, Yury V; Spreizer, Sebastian; Aertsen, Ad; Kumar, Arvind

    2013-01-01

    Can we infer the function of a biological neural network (BNN) if we know the connectivity and activity of all its constituent neurons?This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC). We provide the connectivity and activity of all neurons and invite participants (1) to infer the functions implemented (hard-wired) in spiking neural networks (SNNs) by stimulating and recording the activity of neurons and, (2) to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered.

  10. Autonomous system for pathogen detection and identification

    SciTech Connect

    Belgrader, P.; Benett, W.; Bergman, W.; Langlois, R.; Mariella, R.; Milanovich, F.; Miles, R.; Venkateswaran, K.; Long, G.; Nelson, W.

    1998-09-24

    This purpose of this project is to build a prototype instrument that will, running unattended, detect, identify, and quantify BW agents. In order to accomplish this, we have chosen to start with the world' s leading, proven, assays for pathogens: surface-molecular recognition assays, such as antibody-based assays, implemented on a high-performance, identification (ID)-capable flow cytometer, and the polymerase chain reaction (PCR) for nucleic-acid based assays. With these assays, we must integrate the capability to: l collect samples from aerosols, water, or surfaces; l perform sample preparation prior to the assays; l incubate the prepared samples, if necessary, for a period of time; l transport the prepared, incubated samples to the assays; l perform the assays; l interpret and report the results of the assays. Issues such as reliability, sensitivity and accuracy, quantity of consumables, maintenance schedule, etc. must be addressed satisfactorily to the end user. The highest possible sensitivity and specificity of the assay must be combined with no false alarms. Today, we have assays that can, in under 30 minutes, detect and identify simulants for BW agents at concentrations of a few hundred colony-forming units per ml of solution. If the bio-aerosol sampler of this system collects 1000 Ymin and concentrates the respirable particles into 1 ml of solution with 70% processing efficiency over a period of 5 minutes, then this translates to a detection/ID capability of under 0.1 agent-containing particle/liter of air.

  11. Adaptive Multilevel Middleware for Object Systems

    DTIC Science & Technology

    2006-12-01

    evaluation activities; and introduced and supported a commonly accessible testbed facility to organize and significantly improve multi-technology developer ( TD ...Technology Developers ( TDs ), BBN took on the responsibility of setting up and maintaining an ARMS project within the University of Utah’s Emulab’ system...SYSTEMS The use of the Emulab was a great success, with the majority of the TDs using it at one point or another, and a number using it on a regular basis

  12. An Adaptive Speed Control System for Micro Electro Discharge Machining

    NASA Astrophysics Data System (ADS)

    Yeo, S. H.; Aligiri, E.; Tan, P. C.; Zarepour, H.

    2009-11-01

    The integration of the state-of-the-art monitoring and adaptive control technologies can substantially improve the performance of EDM process. This paper reports the development of an adaptive speed control system for micro EDM which demands a higher level of accuracy. Monitoring of the machining state is conducted during the machining process so that the conditions are analysed continuously. Various schemes for the machining state are used for decision making. For instance, upon recognition of abnormal discharges, the developed adaptive speed control system would adjust the electrode feeding speed in an attempt to correct the machining state. Experimental verification shows that the proposed system can improve the machining time by more than 50%. In addition, a more accurate machined feature can be produced as compared to traditional EDM servo control systems.

  13. HIDEC F-15 adaptive engine control system flight test results

    NASA Technical Reports Server (NTRS)

    Smolka, James W.

    1987-01-01

    NASA-Ames' Highly Integrated Digital Electronic Control (HIDEC) flight test program aims to develop fully integrated airframe, propulsion, and flight control systems. The HIDEC F-15 adaptive engine control system flight test program has demonstrated that significant performance improvements are obtainable through the retention of stall-free engine operation throughout the aircraft flight and maneuver envelopes. The greatest thrust increase was projected for the medium-to-high altitude flight regime at subsonic speed which is of such importance to air combat. Adaptive engine control systems such as the HIDEC F-15's can be used to upgrade the performance of existing aircraft without resort to expensive reengining programs.

  14. Adaptive synchronization of Rossler and Chen chaotic systems

    NASA Astrophysics Data System (ADS)

    Li, Zhi; Han, Chong-Zhao

    2002-07-01

    A novel adaptive synchronization method is proposed for two identical Rossler and Chen systems with uncertain parameters. Based on Lyapunov stability theory, we derive an adaptive controller without the knowledge of the system parameters, which can make the states of two identical Rossler and Chen systems globally asymptotically synchronized. Especially, when some unknown uncertain parameters are positive, we can make the controller more simple and, besides, the controller is independent of those positive uncertain parameters. All results are proved using a well-known Lyapunov stability theorem. Numerical simulations are given to validate the proposed synchronization approach.

  15. Fast calibration of high-order adaptive optics systems.

    PubMed

    Kasper, Markus; Fedrigo, Enrico; Looze, Douglas P; Bonnet, Henri; Ivanescu, Liviu; Oberti, Sylvain

    2004-06-01

    We present a new method of calibrating adaptive optics systems that greatly reduces the required calibration time or, equivalently, improves the signal-to-noise ratio. The method uses an optimized actuation scheme with Hadamard patterns and does not scale with the number of actuators for a given noise level in the wavefront sensor channels. It is therefore highly desirable for high-order systems and/or adaptive secondary systems on a telescope without a Gregorian focal plane. In the latter case, the measurement noise is increased by the effects of the turbulent atmosphere when one is calibrating on a natural guide star.

  16. ADAPTIVE FULL-SPECTRUM SOLOR ENERGY SYSTEMS

    SciTech Connect

    Byard D. Wood

    2004-04-01

    This RD&D project is a three year team effort to develop a hybrid solar lighting (HSL) system that transports solar light from a paraboloidal dish concentrator to a luminaire via a large core polymer fiber optic. The luminaire can be a device to distribute sunlight into a space for the production of algae or it can be a device that is a combination of solar lighting and electric lighting. A benchmark prototype system has been developed to evaluate the HSL system. Sunlight is collected using a one-meter paraboloidal concentrator dish with two-axis tracking. A secondary mirror consisting of eight planar-segmented mirrors directs the visible part of the spectrum to eight fibers (receiver) and subsequently to eight luminaires. This results in about 8,200 lumens incident at each fiber tip. Each fiber can illuminate about 16.7 m{sup 2} (180 ft{sup 2}) of office space. The IR spectrum is directed to a thermophotovoltaic (TPV) array to produce electricity. During this reporting period, the project team made advancements in the design of the second generation (Alpha) system. For the Alpha system, the eight individual 12 mm fibers have been replaced with a centralized bundle of 3 mm fibers. The TRNSYS Full-Spectrum Solar Energy System model has been updated and new components have been added. The TPV array and nonimaging device have been tested and progress has been made in the fiber transmission models. A test plan was developed for both the high-lumen tests and the study to determine the non-energy benefits of daylighting. The photobioreactor team also made major advancements in the testing of model scale and bench top lab-scale systems.

  17. A Model of Internal Communication in Adaptive Communication Systems.

    ERIC Educational Resources Information Center

    Williams, M. Lee

    A study identified and categorized different types of internal communication systems and developed an applied model of internal communication in adaptive organizational systems. Twenty-one large organizations were selected for their varied missions and diverse approaches to managing internal communication. Individual face-to-face or telephone…

  18. Integrating Learning Styles into Adaptive E-Learning System

    ERIC Educational Resources Information Center

    Truong, Huong May

    2015-01-01

    This paper provides an overview and update on my PhD research project which focuses on integrating learning styles into adaptive e-learning system. The project, firstly, aims to develop a system to classify students' learning styles through their online learning behaviour. This will be followed by a study on the complex relationship between…

  19. Adaptive and Optimal Control of Stochastic Dynamical Systems

    DTIC Science & Technology

    2015-09-14

    control and stochastic differential games . Stochastic linear-quadratic, continuous time, stochastic control problems are solved for systems with noise...control problems for systems with arbitrary correlated n 15. SUBJECT TERMS Adaptive control, optimal control, stochastic differential games 16. SECURITY...explicit results have been obtained for problems of stochastic control and stochastic differential games . Stochastic linear- quadratic, continuous time

  20. Understanding leukemic hematopoiesis as a complex adaptive system

    PubMed Central

    Thomas, Xavier

    2015-01-01

    Normal and abnormal hematopoiesis is working as a complex adaptive system. From this perspective, the development and the behavior of hematopoietic cell lineages appear as a balance between normal and abnormal hematopoiesis in the setting of a functioning or malfunctioning microenvironment under the control of the immune system and the influence of hereditary and environmental events. PMID:26516407

  1. Understanding leukemic hematopoiesis as a complex adaptive system.

    PubMed

    Thomas, Xavier

    2015-10-26

    Normal and abnormal hematopoiesis is working as a complex adaptive system. From this perspective, the development and the behavior of hematopoietic cell lineages appear as a balance between normal and abnormal hematopoiesis in the setting of a functioning or malfunctioning microenvironment under the control of the immune system and the influence of hereditary and environmental events.

  2. Multiple-User Adaptive-Array Communication System

    NASA Technical Reports Server (NTRS)

    Zohar, S.

    1985-01-01

    Weights for K-beam system computed K/6 times faster. In single-frequency adaptive-array communication system in whick K mobile users communicate with central station equipped with n-antenna array. Each K signal recoverable by taking specific weighted sum of n complex antenna voltages.

  3. Non-linear system identification in flow-induced vibration

    SciTech Connect

    Spanos, P.D.; Zeldin, B.A.; Lu, R.

    1996-12-31

    The paper introduces a method of identification of non-linear systems encountered in marine engineering applications. The non-linearity is accounted for by a combination of linear subsystems and known zero-memory non-linear transformations; an equivalent linear multi-input-single-output (MISO) system is developed for the identification problem. The unknown transfer functions of the MISO system are identified by assembling a system of linear equations in the frequency domain. This system is solved by performing the Cholesky decomposition of a related matrix. It is shown that the proposed identification method can be interpreted as a {open_quotes}Gram-Schmidt{close_quotes} type of orthogonal decomposition of the input-output quantities of the equivalent MISO system. A numerical example involving the identification of unknown parameters of flow (ocean wave) induced forces on offshore structures elucidates the applicability of the proposed method.

  4. System Identification for the Clipper Liberty C96 Wind Turbine

    NASA Astrophysics Data System (ADS)

    Showers, Daniel

    System identification techniques are powerful tools that help improve modeling capabilities of real world dynamic systems. These techniques are well established and have been successfully used on countless systems in many areas. However, wind turbines provide a unique challenge for system identification because of the difficulty in measuring its primary input: wind. This thesis first motivates the problem by demonstrating the challenges with wind turbine system identification using both simulations and real data. It then suggests techniques toward successfully identifying a dynamic wind turbine model including the notion of an effective wind speed and how it might be measured. Various levels of simulation complexity are explored for insights into calculating an effective wind speed. In addition, measurements taken from the University of Minnesota's Clipper Liberty C96 research wind turbine are used for a preliminary investigation into the effective wind speed calculation and system identification of a real world wind turbine.

  5. Network adaptable information systems for safeguard applications

    SciTech Connect

    Rodriguez, C.; Burczyk, L.; Chare, P.; Wagner, H.

    1996-09-01

    While containment and surveillance systems designed for nuclear safeguards have greatly improved through advances in computer, sensor, and microprocessor technologies, the authors recognize the need to continue the advancement of these systems to provide more standardized solutions for safeguards applications of the future. The benefits to be gained from the use of standardized technologies are becoming evident as safeguard activities are increasing world-wide while funding of these activities is becoming more limited. The EURATOM Safeguards Directorate and Los Alamos National Laboratory are developing and testing advanced monitoring technologies coupled with the most efficient solutions for the safeguards applications of the future.

  6. Framework for Adaptable Operating and Runtime Systems: Final Project Report

    SciTech Connect

    Patrick G. Bridges

    2012-02-01

    In this grant, we examined a wide range of techniques for constructing high-performance con gurable system software for HPC systems and its application to DOE-relevant problems. Overall, research and development on this project focused in three specifc areas: (1) software frameworks for constructing and deploying con gurable system software, (2) applcation of these frameworks to HPC-oriented adaptable networking software, (3) performance analysis of HPC system software to understand opportunities for performance optimization.

  7. Method and system for environmentally adaptive fault tolerant computing

    NASA Technical Reports Server (NTRS)

    Copenhaver, Jason L. (Inventor); Jeremy, Ramos (Inventor); Wolfe, Jeffrey M. (Inventor); Brenner, Dean (Inventor)

    2010-01-01

    A method and system for adapting fault tolerant computing. The method includes the steps of measuring an environmental condition representative of an environment. An on-board processing system's sensitivity to the measured environmental condition is measured. It is determined whether to reconfigure a fault tolerance of the on-board processing system based in part on the measured environmental condition. The fault tolerance of the on-board processing system may be reconfigured based in part on the measured environmental condition.

  8. Lessons from Adaptive Level One Accelerator (ALOA) System Implementation

    NASA Technical Reports Server (NTRS)

    Patel, Umesh D.; Brambora, Clifford; Ghuman, Parminder; Day, John H. (Technical Monitor)

    2001-01-01

    The Adaptive Level One Accelerator (ALOA) system was developed as part of the Earth Science Data and Information System (ESDIS) project. The reconfigurable computing technologies were investigated for Level 1 satellite telemetry data processing to achieve computing acceleration and cost reduction for the next-generation Level 1 data processing systems. The MODIS instrument calibration algorithm was implemented using reconfigurable a computer. The system development process and the lessons learned throughout the design cycle are summarized in this paper.

  9. Climate change: Cropping system changes and adaptations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Climate change impacts the life of every person; however, there is little comprehensive understanding of the direct and indirect effects of climate change on agriculture. Since our food, feed, fiber, and fruit is derived from agricultural systems, understanding the effects of changing temperature, p...

  10. Adaptive Device Context Based Mobile Learning Systems

    ERIC Educational Resources Information Center

    Pu, Haitao; Lin, Jinjiao; Song, Yanwei; Liu, Fasheng

    2011-01-01

    Mobile learning is e-learning delivered through mobile computing devices, which represents the next stage of computer-aided, multi-media based learning. Therefore, mobile learning is transforming the way of traditional education. However, as most current e-learning systems and their contents are not suitable for mobile devices, an approach for…

  11. Robust Adaptive Control of Multivariable Nonlinear Systems

    DTIC Science & Technology

    2011-03-28

    Systems: Challenge Problem Integration and NASA s Integrated Resilient Aircraft Control . We also revealed some similarities with the disturbance ... observer (DOB) controllers and identified the main features in the difference between them. The key feature of this difference is that the estimation loop

  12. The Moon System Adapted for Musical Notation.

    ERIC Educational Resources Information Center

    Jackson, Michael

    1987-01-01

    A means is presented for using William Moon's embossed symbols to represent musical notation for blind individuals, as an alternative to braille notation. The proposed system includes pitch symbols, octave indicators, duration symbols, accidentals, key signatures, rests, stress symbols, ornaments, and other symbols. (Author/JDD)

  13. Adaptive control with an expert system based supervisory level. Thesis

    NASA Technical Reports Server (NTRS)

    Sullivan, Gerald A.

    1991-01-01

    Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up

  14. Effects of adaptive task allocation on monitoring of automated systems.

    PubMed

    Parasuraman, R; Mouloua, M; Molloy, R

    1996-12-01

    The effects of adaptive task allocation on monitoring for automation failure during multitask flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 30-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator ("human control"), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the 10-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.

  15. Adaptive Management of Computing and Network Resources for Spacecraft Systems

    NASA Technical Reports Server (NTRS)

    Pfarr, Barbara; Welch, Lonnie R.; Detter, Ryan; Tjaden, Brett; Huh, Eui-Nam; Szczur, Martha R. (Technical Monitor)

    2000-01-01

    It is likely that NASA's future spacecraft systems will consist of distributed processes which will handle dynamically varying workloads in response to perceived scientific events, the spacecraft environment, spacecraft anomalies and user commands. Since all situations and possible uses of sensors cannot be anticipated during pre-deployment phases, an approach for dynamically adapting the allocation of distributed computational and communication resources is needed. To address this, we are evolving the DeSiDeRaTa adaptive resource management approach to enable reconfigurable ground and space information systems. The DeSiDeRaTa approach embodies a set of middleware mechanisms for adapting resource allocations, and a framework for reasoning about the real-time performance of distributed application systems. The framework and middleware will be extended to accommodate (1) the dynamic aspects of intra-constellation network topologies, and (2) the complete real-time path from the instrument to the user. We are developing a ground-based testbed that will enable NASA to perform early evaluation of adaptive resource management techniques without the expense of first deploying them in space. The benefits of the proposed effort are numerous, including the ability to use sensors in new ways not anticipated at design time; the production of information technology that ties the sensor web together; the accommodation of greater numbers of missions with fewer resources; and the opportunity to leverage the DeSiDeRaTa project's expertise, infrastructure and models for adaptive resource management for distributed real-time systems.

  16. Automated frequency domain system identification of a large space structure

    NASA Technical Reports Server (NTRS)

    Yam, Y.; Bayard, D. S.; Hadaegh, F. Y.; Mettler, E.; Milman, M. H.

    1989-01-01

    This paper presents the development and experimental results of an automated on-orbit system identification method for large flexible spacecraft that yields estimated quantities to support on-line design and tuning of robust high performance control systems. The procedure consists of applying an input to the plant, obtaining an output, and then conducting nonparametric identification to yield the spectral estimate of the system transfer function. A parametric model is determined by curve fitting the spectral estimate to a rational transfer function. The identification method has been demonstrated experimentally on the Large Spacecraft Control Laboratory in JPL.

  17. Substructure System Identification for Finite Element Model Updating

    NASA Technical Reports Server (NTRS)

    Craig, Roy R., Jr.; Blades, Eric L.

    1997-01-01

    This report summarizes research conducted under a NASA grant on the topic 'Substructure System Identification for Finite Element Model Updating.' The research concerns ongoing development of the Substructure System Identification Algorithm (SSID Algorithm), a system identification algorithm that can be used to obtain mathematical models of substructures, like Space Shuttle payloads. In the present study, particular attention was given to the following topics: making the algorithm robust to noisy test data, extending the algorithm to accept experimental FRF data that covers a broad frequency bandwidth, and developing a test analytical model (TAM) for use in relating test data to reduced-order finite element models.

  18. Adaptation in the innate immune system and heterologous innate immunity.

    PubMed

    Martin, Stefan F

    2014-11-01

    The innate immune system recognizes deviation from homeostasis caused by infectious or non-infectious assaults. The threshold for its activation seems to be established by a calibration process that includes sensing of microbial molecular patterns from commensal bacteria and of endogenous signals. It is becoming increasingly clear that adaptive features, a hallmark of the adaptive immune system, can also be identified in the innate immune system. Such adaptations can result in the manifestation of a primed state of immune and tissue cells with a decreased activation threshold. This keeps the system poised to react quickly. Moreover, the fact that the innate immune system recognizes a wide variety of danger signals via pattern recognition receptors that often activate the same signaling pathways allows for heterologous innate immune stimulation. This implies that, for example, the innate immune response to an infection can be modified by co-infections or other innate stimuli. This "design feature" of the innate immune system has many implications for our understanding of individual susceptibility to diseases or responsiveness to therapies and vaccinations. In this article, adaptive features of the innate immune system as well as heterologous innate immunity and their implications are discussed.

  19. An Approach to V&V of Embedded Adaptive Systems

    NASA Technical Reports Server (NTRS)

    Liu, Yan; Yerramalla, Sampath; Fuller, Edgar; Cukic, Bojan; Gururajan, Srikaruth

    2004-01-01

    Rigorous Verification and Validation (V&V) techniques are essential for high assurance systems. Lately, the performance of some of these systems is enhanced by embedded adaptive components in order to cope with environmental changes. Although the ability of adapting is appealing, it actually poses a problem in terms of V&V. Since uncertainties induced by environmental changes have a significant impact on system behavior, the applicability of conventional V&V techniques is limited. In safety-critical applications such as flight control system, the mechanisms of change must be observed, diagnosed, accommodated and well understood prior to deployment. In this paper, we propose a non-conventional V&V approach suitable for online adaptive systems. We apply our approach to an intelligent flight control system that employs a particular type of Neural Networks (NN) as the adaptive learning paradigm. Presented methodology consists of a novelty detection technique and online stability monitoring tools. The novelty detection technique is based on Support Vector Data Description that detects novel (abnormal) data patterns. The Online Stability Monitoring tools based on Lyapunov's Stability Theory detect unstable learning behavior in neural networks. Cases studies based on a high fidelity simulator of NASA's Intelligent Flight Control System demonstrate a successful application of the presented V&V methodology. ,

  20. Adaptive carrier recovery systems for digital data communications receivers

    NASA Astrophysics Data System (ADS)

    Cupo, Robert L.; Gitlin, Richard D.

    1989-12-01

    Adaptive or predictive carrier recovery systems, which are essential in high-performance quadrature-amplitude-modulated (QAM) data communications systems to correct for phase jitter and frequency offset, are considered. Analytical and experimental results are presented for two structures that implement a predictive carrier recovery system. These systems, which adapt their structure to match the spectral properties of the impairments, avoid the conflict between a wide bandwidth (to track fast jitter) and a narrow bandwidth (to minimize output noise) inherent in most carrier recovery loops. Such a system increases the likelihood that very bandwidth-efficient modems (e.g., 7 bits/s/Hz for 19.2 kbits/s voiceband modem applications) can provide reliable transmission in the presence of severe phase jitter and frequency offset. In particular, the predictive carrier recovery systems can track sinusoidal jitter present at more than one frequency as well as generalized time-varying phase jitter processes. Both finite-impulse-response and infinite-impulse-response (IIR) adaptive phase tracking systems are considered. Prior limitations on adaptive IIR filters are overcome by designing a structure that is guaranteed to be stable and to possess only a global minimum as the filter coefficients converge to their desired values.

  1. Adaptive optics at Lick Observatory: System architecture and operations

    SciTech Connect

    Brase, J.M.; An, J.; Avicola, K.

    1994-03-01

    We will describe an adaptive optics system developed for the 1 meter Nickel and 3 meter Shane telescopes at Lick Observatory. Observing wavelengths will be in the visible for the 1 meter telescope and in the near IR on the 3 meter. The adaptive optics system design is based on a 69 actuator continuous surface deformable mirror and a Hartmann wavefront sensor equipped with an intensified CCD framing camera. The system has been tested at the Cassegrain focus of the 1 meter telescope where the subaperture size is 12.5 cm. The wavefront control calculations are performed on a four processor single board computer controlled by a Unix-based system. We will describe the optical system and give details of the wavefront control system design. We will present predictions of the system performance and initial test results.

  2. Adaptive optics at Lick Observatory: system architecture and operations

    NASA Astrophysics Data System (ADS)

    Brase, James M.; An, Jong; Avicola, Kenneth; Bissinger, Horst D.; Friedman, Herbert W.; Gavel, Donald T.; Johnston, Brooks; Max, Claire E.; Olivier, Scot S.; Presta, Robert W.; Rapp, David A.; Salmon, J. Thaddeus; Waltjen, Kenneth E.; Fisher, William A.

    1994-05-01

    We will describe an adaptive optics system developed for the 1 meter Nickel and 3 meter Shane telescopes at Lick Observatory. Observing wavelengths will be in the visible for the 1 meter telescope and in the near IR on the 3 meter. The adaptive optics system design is based on a 69 actuator continuous surface deformable mirror and a Hartmann wavefront sensor equipped with an intensified CCD framing camera. The system has been tested at the Cassegrain focus of the 1 meter telescope where the subaperture size is 12.5 cm. The wavefront control calculations are performed on a four processor single board computer controlled by a Unix-based system. We will describe the optical system and give details of the wavefront control system design. We will present predictions of the system performance and initial test results.

  3. SDR implementation of the receiver of adaptive communication system

    NASA Astrophysics Data System (ADS)

    Skarzynski, Jacek; Darmetko, Marcin; Kozlowski, Sebastian; Kurek, Krzysztof

    2016-04-01

    The paper presents software implementation of a receiver forming a part of an adaptive communication system. The system is intended for communication with a satellite placed in a low Earth orbit (LEO). The ability of adaptation is believed to increase the total amount of data transmitted from the satellite to the ground station. Depending on the signal-to-noise ratio (SNR) of the received signal, adaptive transmission is realized using different transmission modes, i.e., different modulation schemes (BPSK, QPSK, 8-PSK, and 16-APSK) and different convolutional code rates (1/2, 2/3, 3/4, 5/6, and 7/8). The receiver consists of a software-defined radio (SDR) module (National Instruments USRP-2920) and a multithread reception software running on Windows operating system. In order to increase the speed of signal processing, the software takes advantage of single instruction multiple data instructions supported by x86 processor architecture.

  4. Laser Adaptive System for Measurement of Molecule Mass and Concentration

    NASA Astrophysics Data System (ADS)

    Romashko, R. V.; Kulchin, Y. N.; Efimov, T. A.; Sergeev, A. A.; Nepomnyashiy, A. V.

    A Laser adaptive microweighting system for measurement of molecules mass based on the principles of adaptive holog aphic interferometry is proposed and experimentally tested in task of gas concentration measurement. A sensitive element of the system is a microcantilever coated by a layer of chitosan, which can adsorb different molecules. Changes in gas concentration re ult in change in mass of molecules adsorbed in chitosan, and, as sequence, result in change in natural frequency of cantilever oscillations, which are measured by an adaptive holographic interferometer. The operation of the system has been experimentally demonstrated in measurement of water vapor concentration. The detected change in concentration of H2O molecules amounted to 125 ppm.

  5. Adaptive synchronization of two chaotic systems with stochastic unknown parameters

    NASA Astrophysics Data System (ADS)

    Salarieh, Hassan; Alasty, Aria

    2009-02-01

    Using the Lyapunov stability theory an adaptive control is proposed for chaos synchronization between two different systems which have stochastically time varying unknown coefficients. The stochastic variations of the coefficients about their unknown mean values are modeled through white Gaussian noise produced by the Weiner process. It is shown that using the proposed adaptive control the mean square of synchronization error converges to an arbitrarily small bound around zero. To demonstrate the effectiveness of the proposed technique, it is applied to the Lorenz-Chen and the Chen-Rossler dynamical systems, as some case studies. Simulation results indicate that the proposed adaptive controller has a high performance in synchronization of chaotic systems in noisy environment.

  6. An adaptive brain actuated system for augmenting rehabilitation

    PubMed Central

    Roset, Scott A.; Gant, Katie; Prasad, Abhishek; Sanchez, Justin C.

    2014-01-01

    For people living with paralysis, restoration of hand function remains the top priority because it leads to independence and improvement in quality of life. In approaches to restore hand and arm function, a goal is to better engage voluntary control and counteract maladaptive brain reorganization that results from non-use. Standard rehabilitation augmented with developments from the study of brain-computer interfaces could provide a combined therapy approach for motor cortex rehabilitation and to alleviate motor impairments. In this paper, an adaptive brain-computer interface system intended for application to control a functional electrical stimulation (FES) device is developed as an experimental test bed for augmenting rehabilitation with a brain-computer interface. The system's performance is improved throughout rehabilitation by passive user feedback and reinforcement learning. By continuously adapting to the user's brain activity, similar adaptive systems could be used to support clinical brain-computer interface neurorehabilitation over multiple days. PMID:25565945

  7. Software Technology for Adaptable, Reliable Systems (STARS)

    DTIC Science & Technology

    1990-11-02

    through the use of a single intermediate language. However, certain evolutionary paths, i.e., translators and funtional interfaces, must be established...Systems Ada compiler beginning in December 1984 and was presented at an Arcadia consortium meeting held in December 1984. Iris concepts and a grammar ...Page 11 2 November 1990 STARS-RC-01430/001/00 o An LALR parser generator and an Ada grammar , used to produce the parse phase of the Ada-to-DIANA

  8. ADAPTIVE CLEARANCE CONTROL SYSTEMS FOR TURBINE ENGINES

    NASA Technical Reports Server (NTRS)

    Blackwell, Keith M.

    2004-01-01

    The Controls and Dynamics Technology Branch at NASA Glenn Research Center primarily deals in developing controls, dynamic models, and health management technologies for air and space propulsion systems. During the summer of 2004 I was granted the privilege of working alongside professionals who were developing an active clearance control system for commercial jet engines. Clearance, the gap between the turbine blade tip and the encompassing shroud, increases as a result of wear mechanisms and rubbing of the turbine blades on shroud. Increases in clearance cause larger specific fuel consumption (SFC) and loss of efficient air flow. This occurs because, as clearances increase, the engine must run hotter and bum more fuel to achieve the same thrust. In order to maintain efficiency, reduce fuel bum, and reduce exhaust gas temperature (EGT), the clearance must be accurately controlled to gap sizes no greater than a few hundredths of an inch. To address this problem, NASA Glenn researchers have developed a basic control system with actuators and sensors on each section of the shroud. Instead of having a large uniform metal casing, there would be sections of the shroud with individual sensors attached internally that would move slightly to reform and maintain clearance. The proposed method would ultimately save the airline industry millions of dollars.

  9. Effects of Age and Cognition on a Cross-Cultural Paediatric Adaptation of the Sniffin' Sticks Identification Test

    PubMed Central

    Guerreiro, Marilisa Mantovani; Lees, Andrew John; Warner, Thomas T.

    2015-01-01

    Objectives To study the effects of age and cognition on the performance of children aged 3 to 18 years on a culturally adapted version of the 16 item smell identification test from Sniffin' Sticks (SS16). Methods A series of pilots were conducted on 29 children aged 3 to 18 years old and 23 adults to produce an adapted version of the SS16 suitable for Brazilian children (SS16-Child). A final version was applied to 51 children alongside a picture identification test (PIT-SS16-Child) to access cognitive abilities involved in the smell identification task. In addition 20 adults performed the same tasks as a comparison group. Results The final adapted SS16-Child was applied to 51 children with a mean age of 9.9 years (range 3-18 years, SD=4.25 years), of which 68.3% were girls. There was an independent effect of age (p<0.05) and PIT-SS16-Child (p<0.001) on the performance on the SS16-Child, and older children reached the ceiling for scoring in the cognitive and olfactory test. Pre-school children had difficulties identifying items of the test. Discussion/Conclusions A cross-culturally adapted version of the SS16 can be used to test olfaction in children but interpretation of the results must take age and cognitive abilities into consideration. PMID:26267145

  10. Adaptation.

    PubMed

    Broom, Donald M

    2006-01-01

    The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and

  11. Situational adapting system supporting team situation awareness

    NASA Astrophysics Data System (ADS)

    Helldin, Tove; Erlandsson, Tina; Niklasson, Lars; Falkman, Göran

    2010-10-01

    Military fighter pilots have to make suitable decisions fast in an environment where continuously increasing flows of information from sensors, team members and databases are provided. Not only do the huge amounts of data aggravate the pilots' decision making process: time-pressure, presence of uncertain data and high workload are factors that can worsen the performance of pilot decision making. In this paper, initial ideas of how to support the pilots accomplishing their tasks are presented. Results from interviews with two fighter pilots are described as well as a discussion about how these results can guide the design of a military fighter pilot decision support system, with focus on team cooperation.

  12. Real-time control system for adaptive resonator

    SciTech Connect

    Flath, L; An, J; Brase, J; Hurd, R; Kartz, M; Sawvel, R; Silva, D

    2000-07-24

    Sustained operation of high average power solid-state lasers currently requires an adaptive resonator to produce the optimal beam quality. We describe the architecture of a real-time adaptive control system for correcting intra-cavity aberrations in a heat capacity laser. Image data collected from a wavefront sensor are processed and used to control phase with a high-spatial-resolution deformable mirror. Our controller takes advantage of recent developments in low-cost, high-performance processor technology. A desktop-based computational engine and object-oriented software architecture replaces the high-cost rack-mount embedded computers of previous systems.

  13. Design of suboptimal adaptive filter for stochastic systems

    NASA Astrophysics Data System (ADS)

    Ahn, Jun Il; Shin, Vladimir

    2005-12-01

    In this paper, the problem of estimating the system state in for linear discrete-time systems with uncertainties is considered. In [1], [2], we have proposed the fusion formula (FF) for an arbitrary number of correlated and uncorrelated estimates. The FF is applied to detection and filtering problem. The new suboptimal adaptive filter with parallel structure is herein proposed. In consequence of parallel structure of the proposed filter, parallel computers can be used for their design. A lower computational complexity and lower memory demand are achieved with the proposed filter than in the optimal adaptive Lainiotis-Kalman filter. Example demonstrates the accuracy of the new filter.

  14. Parameter estimation techniques for LTP system identification

    NASA Astrophysics Data System (ADS)

    Nofrarias Serra, Miquel

    LISA Pathfinder (LPF) is the precursor mission of LISA (Laser Interferometer Space Antenna) and the first step towards gravitational waves detection in space. The main instrument onboard the mission is the LTP (LISA Technology Package) whose scientific goal is to test LISA's drag-free control loop by reaching a differential acceleration noise level between two masses in √ geodesic motion of 3 × 10-14 ms-2 / Hz in the milliHertz band. The mission is not only challenging in terms of technology readiness but also in terms of data analysis. As with any gravitational wave detector, attaining the instrument performance goals will require an extensive noise hunting campaign to measure all contributions with high accuracy. But, opposite to on-ground experiments, LTP characterisation will be only possible by setting parameters via telecommands and getting a selected amount of information through the available telemetry downlink. These two conditions, high accuracy and high reliability, are the main restrictions that the LTP data analysis must overcome. A dedicated object oriented Matlab Toolbox (LTPDA) has been set up by the LTP analysis team for this purpose. Among the different toolbox methods, an essential part for the mission are the parameter estimation tools that will be used for system identification during operations: Linear Least Squares, Non-linear Least Squares and Monte Carlo Markov Chain methods have been implemented as LTPDA methods. The data analysis team has been testing those methods with a series of mock data exercises with the following objectives: to cross-check parameter estimation methods and compare the achievable accuracy for each of them, and to develop the best strategies to describe the physics underlying a complex controlled experiment as the LTP. In this contribution we describe how these methods were tested with simulated LTP-like data to recover the parameters of the model and we report on the latest results of these mock data exercises.

  15. Evolution of innate and adaptive immune systems in jawless vertebrates.

    PubMed

    Kasamatsu, Jun

    2013-01-01

    Because jawless vertebrates are the most primitive vertebrates, they have been studied to gain understanding of the evolutionary processes that gave rise to the innate and adaptive immune systems in vertebrates. Jawless vertebrates have developed lymphocyte-like cells that morphologically resemble the T and B cells of jawed vertebrates, but they express variable lymphocyte receptors (VLRs) instead of the T and B cell receptors that specifically recognize antigens in jawed vertebrates. These VLRs act as antigen receptors, diversity being generated in their antigen-binding sites by assembly of highly diverse leucine-rich repeat modules. Therefore, jawless vertebrates have developed adaptive immune systems based on the VLRs. Although pattern recognition receptors, including Toll-like receptors (TLRs) and Rig-like receptors (RLRs), and their adaptor genes are conserved in jawless vertebrates, some transcription factor and inflammatory cytokine genes in the TLR and RLR pathways are not present. However, like jawed vertebrates, the initiation of adaptive immune responses in jawless vertebrates appears to require prior activation of the innate immune system. These observations imply that the innate immune systems of jawless vertebrates have a unique molecular basis that is distinct from that of jawed vertebrates. Altogether, although the molecular details of the innate and adaptive immune systems differ between jawless and jawed vertebrates, jawless vertebrates have developed versions of these immune systems that are similar to those of jawed vertebrates.

  16. Adaptive Modeling of the International Space Station Electrical Power System

    NASA Technical Reports Server (NTRS)

    Thomas, Justin Ray

    2007-01-01

    Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

  17. Adaptive mass expulsion attitude control system

    NASA Technical Reports Server (NTRS)

    Rodden, John J. (Inventor); Stevens, Homer D. (Inventor); Carrou, Stephane (Inventor)

    2001-01-01

    An attitude control system and method operative with a thruster controls the attitude of a vehicle carrying the thruster, wherein the thruster has a valve enabling the formation of pulses of expelled gas from a source of compressed gas. Data of the attitude of the vehicle is gathered, wherein the vehicle is located within a force field tending to orient the vehicle in a first attitude different from a desired attitude. The attitude data is evaluated to determine a pattern of values of attitude of the vehicle in response to the gas pulses of the thruster and in response to the force field. The system and the method maintain the attitude within a predetermined band of values of attitude which includes the desired attitude. Computation circuitry establishes an optimal duration of each of the gas pulses based on the pattern of values of attitude, the optimal duration providing for a minimal number of opening and closure operations of the valve. The thruster is operated to provide gas pulses having the optimal duration.

  18. Adaptive data acquisition multiplexing system and method

    NASA Technical Reports Server (NTRS)

    Sinderson, Richard L. (Inventor); Salazar, George A. (Inventor); Haddick, Clyde M., Jr. (Inventor); Spahn, Caroll J. (Inventor); Venkatesh, Chikkabelarangala N. (Inventor)

    1990-01-01

    A reconfigurable telemetry multiplexer is described which includes a monitor-terminal and a plurality of remote terminals. The remote terminals each include signal conditioning for a plurality of sensors for measuring parameters which are converted by an analog to digital converter. CPU's in the remote terminals store instructions for prompting system configuration and reconfiguration commands. The measurements, instructions, and the terminal's present configuration and status data are transmitted to the monitor-terminal and displayed. In response to menu-driven prompts generated and displayed at the monitor-terminal, data generation request commands, status and health commands, and the like are input at the monitor-terminal and transmitted to the remote terminals. The CPU in each remote terminal receives the various commands, stores them in electrically alterable memory, and reacts in accordance with the commands to reconfigure a plurality of aspects of the system. The CPU in each terminal also generates parameter measurements, status and health signals, and transmits these signals of the respective terminals to the monitor-terminal for low data rate operator viewing and to higher rate external transmission/monitor equipment. Reconfiguration may be in real time during the general period of parameter measurement acquisition, and may include alteration of the gain, automatic gain rescaling, bias, and or sampling rates associated with one or more of the parameter measurements made by the remote terminals.

  19. Quantitative adaptation analytics for assessing dynamic systems of systems: LDRD Final Report

    SciTech Connect

    Gauthier, John H.; Miner, Nadine E.; Wilson, Michael L.; Le, Hai D.; Kao, Gio K.; Melander, Darryl J.; Longsine, Dennis Earl; Vander Meer, Jr., Robert C.

    2015-01-01

    Our society is increasingly reliant on systems and interoperating collections of systems, known as systems of systems (SoS). These SoS are often subject to changing missions (e.g., nation- building, arms-control treaties), threats (e.g., asymmetric warfare, terrorism), natural environments (e.g., climate, weather, natural disasters) and budgets. How well can SoS adapt to these types of dynamic conditions? This report details the results of a three year Laboratory Directed Research and Development (LDRD) project aimed at developing metrics and methodologies for quantifying the adaptability of systems and SoS. Work products include: derivation of a set of adaptability metrics, a method for combining the metrics into a system of systems adaptability index (SoSAI) used to compare adaptability of SoS designs, development of a prototype dynamic SoS (proto-dSoS) simulation environment which provides the ability to investigate the validity of the adaptability metric set, and two test cases that evaluate the usefulness of a subset of the adaptability metrics and SoSAI for distinguishing good from poor adaptability in a SoS. Intellectual property results include three patents pending: A Method For Quantifying Relative System Adaptability, Method for Evaluating System Performance, and A Method for Determining Systems Re-Tasking.

  20. Development of adaptive control applied to chaotic systems

    NASA Astrophysics Data System (ADS)

    Rhode, Martin Andreas

    1997-12-01

    Continuous-time derivative control and adaptive map-based recursive feedback control techniques are used to control chaos in a variety of systems and in situations that are of practical interest. The theoretical part of the research includes the review of fundamental concept of control theory in the context of its applications to deterministic chaotic systems, the development of a new adaptive algorithm to identify the linear system properties necessary for control, and the extension of the recursive proportional feedback control technique, RPF, to high dimensional systems. Chaos control was applied to models of a thermal pulsed combustor, electro-chemical dissolution and the hyperchaotic Rossler system. Important implications for combustion engineering were suggested by successful control of the model of the thermal pulsed combustor. The system was automatically tracked while maintaining control into regions of parameter and state space where no stable attractors exist. In a simulation of the electrochemical dissolution system, application of derivative control to stabilize a steady state, and adaptive RPF to stabilize a period one orbit, was demonstrated. The high dimensional adaptive control algorithm was applied in a simulation using the Rossler hyperchaotic system, where a period-two orbit with two unstable directions was stabilized and tracked over a wide range of a system parameter. In the experimental part, the electrochemical system was studied in parameter space, by scanning the applied potential and the frequency of the rotating copper disk. The automated control algorithm is demonstrated to be effective when applied to stabilize a period-one orbit in the experiment. We show the necessity of small random perturbations applied to the system in order to both learn the dynamics and control the system at the same time. The simultaneous learning and control capability is shown to be an important part of the active feedback control.

  1. Decision-making in healthcare as a complex adaptive system.

    PubMed

    Kuziemsky, Craig

    2016-01-01

    Healthcare transformation requires a change in how the business of healthcare is done. Traditional decision-making approaches based on stable and predictable systems are inappropriate in healthcare because of the complex nature of healthcare delivery. This article reviews challenges to using traditional decision-making approaches in healthcare and how insight from Complex Adaptive Systems (CAS) could support healthcare management. The article also provides a system model to guide decision-making in healthcare as a CAS.

  2. Modeling of Biometric Identification System Using the Colored Petri Nets

    NASA Astrophysics Data System (ADS)

    Petrosyan, G. R.; Ter-Vardanyan, L. A.; Gaboutchian, A. V.

    2015-05-01

    In this paper we present a model of biometric identification system transformed into Petri Nets. Petri Nets, as a graphical and mathematical tool, provide a uniform environment for modelling, formal analysis, and design of discrete event systems. The main objective of this paper is to introduce the fundamental concepts of Petri Nets to the researchers and practitioners, both from identification systems, who are involved in the work in the areas of modelling and analysis of biometric identification types of systems, as well as those who may potentially be involved in these areas. In addition, the paper introduces high-level Petri Nets, as Colored Petri Nets (CPN). In this paper the model of Colored Petri Net describes the identification process much simpler.

  3. 47 CFR 25.281 - Automatic Transmitter Identification System (ATIS).

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... (ATIS). 25.281 Section 25.281 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Technical Operations § 25.281 Automatic Transmitter Identification System (ATIS). All satellite uplink transmissions carrying broadband video information shall...

  4. 47 CFR 25.281 - Automatic Transmitter Identification System (ATIS).

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... (ATIS). 25.281 Section 25.281 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Technical Operations § 25.281 Automatic Transmitter Identification System (ATIS). All satellite uplink transmissions carrying broadband video information shall...

  5. 47 CFR 25.281 - Automatic Transmitter Identification System (ATIS).

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... (ATIS). 25.281 Section 25.281 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Technical Operations § 25.281 Automatic Transmitter Identification System (ATIS). All satellite uplink transmissions carrying broadband video information shall...

  6. Self-characterization of linear and nonlinear adaptive optics systems

    NASA Astrophysics Data System (ADS)

    Hampton, Peter J.; Conan, Rodolphe; Keskin, Onur; Bradley, Colin; Agathoklis, Pan

    2008-01-01

    We present methods used to determine the linear or nonlinear static response and the linear dynamic response of an adaptive optics (AO) system. This AO system consists of a nonlinear microelectromechanical systems deformable mirror (DM), a linear tip-tilt mirror (TTM), a control computer, and a Shack-Hartmann wavefront sensor. The system is modeled using a single-input-single-output structure to determine the one-dimensional transfer function of the dynamic response of the chain of system hardware. An AO system has been shown to be able to characterize its own response without additional instrumentation. Experimentally determined models are given for a TTM and a DM.

  7. [Caffeine and adaptive changes in the circulatory system during pregnancy].

    PubMed

    Cendrowska-Pinkosz, Monika; Dworzański, Wojciech; Krauze, Magdalena; Burdan, Franciszek

    2017-01-23

    Adaptive physiological changes that occur in pregnant women can fluctuate with the intake of substances with proven, adverse biological effect on the body. Due to the fact that caffeine is one of the most chronically used xenobiotics, the impact of consuming caffeine on adaptive processes in the circulatory system of a pregnant women required a research. Many researchers emphasise its negative effect on the circulatory system of the mother and her offspring. However, in spite of years of observation, there is no clear answer to what extent dose or in what period of time the caffeine modulates the adaptive processes during pregnancy. Because of the potential risk the supply of caffeine during pregnancy should be subjected to considerable restrictions.

  8. A dual-modal retinal imaging system with adaptive optics

    PubMed Central

    Meadway, Alexander; Girkin, Christopher A.; Zhang, Yuhua

    2013-01-01

    An adaptive optics scanning laser ophthalmoscope (AO-SLO) is adapted to provide optical coherence tomography (OCT) imaging. The AO-SLO function is unchanged. The system uses the same light source, scanning optics, and adaptive optics in both imaging modes. The result is a dual-modal system that can acquire retinal images in both en face and cross-section planes at the single cell level. A new spectral shaping method is developed to reduce the large sidelobes in the coherence profile of the OCT imaging when a non-ideal source is used with a minimal introduction of noise. The technique uses a combination of two existing digital techniques. The thickness and position of the traditionally named inner segment/outer segment junction are measured from individual photoreceptors. In-vivo images of healthy and diseased human retinas are demonstrated. PMID:24514529

  9. Adapting ISA system warnings to enhance user acceptance.

    PubMed

    Jiménez, Felipe; Liang, Yingzhen; Aparicio, Francisco

    2012-09-01

    Inappropriate speed is a major cause of traffic accidents. Different measures have been considered to control traffic speed, and intelligent speed adaptation (ISA) systems are one of the alternatives. These systems know the speed limits and try to improve compliance with them. This paper deals with an informative ISA system that provides the driver with an advance warning before reaching a road section with singular characteristics that require a lower safe speed than the current speed. In spite of the extensive tests performed using ISA systems, few works show how warnings can be adapted to the driver. This paper describes a method to adapt warning parameters (safe speed on curves, zone of influence of a singular stretch, deceleration process and reaction time) to normal driving behavior. The method is based on a set of tests with and without the ISA system. This adjustment, as well as the analysis of driver acceptance before and after the adaptation and changes in driver behavior (changes in speed and path) resulting from the tested ISA regarding a driver's normal driving style, is shown in this paper. The main conclusion is that acceptance by drivers increased significantly after redefining the warning parameters, but the effect of speed homogenization was not reduced.

  10. Development of an Automatic Identification System Autonomous Positioning System.

    PubMed

    Hu, Qing; Jiang, Yi; Zhang, Jingbo; Sun, Xiaowen; Zhang, Shufang

    2015-11-11

    In order to overcome the vulnerability of the global navigation satellite system (GNSS) and provide robust position, navigation and time (PNT) information in marine navigation, the autonomous positioning system based on ranging-mode Automatic Identification System (AIS) is presented in the paper. The principle of the AIS autonomous positioning system (AAPS) is investigated, including the position algorithm, the signal measurement technique, the geometric dilution of precision, the time synchronization technique and the additional secondary factor correction technique. In order to validate the proposed AAPS, a verification system has been established in the Xinghai sea region of Dalian (China). Static and dynamic positioning experiments are performed. The original function of the AIS in the AAPS is not influenced. The experimental results show that the positioning precision of the AAPS is better than 10 m in the area with good geometric dilution of precision (GDOP) by the additional secondary factor correction technology. This is the most economical solution for a land-based positioning system to complement the GNSS for the navigation safety of vessels sailing along coasts.

  11. Development of an Automatic Identification System Autonomous Positioning System

    PubMed Central

    Hu, Qing; Jiang, Yi; Zhang, Jingbo; Sun, Xiaowen; Zhang, Shufang

    2015-01-01

    In order to overcome the vulnerability of the global navigation satellite system (GNSS) and provide robust position, navigation and time (PNT) information in marine navigation, the autonomous positioning system based on ranging-mode Automatic Identification System (AIS) is presented in the paper. The principle of the AIS autonomous positioning system (AAPS) is investigated, including the position algorithm, the signal measurement technique, the geometric dilution of precision, the time synchronization technique and the additional secondary factor correction technique. In order to validate the proposed AAPS, a verification system has been established in the Xinghai sea region of Dalian (China). Static and dynamic positioning experiments are performed. The original function of the AIS in the AAPS is not influenced. The experimental results show that the positioning precision of the AAPS is better than 10 m in the area with good geometric dilution of precision (GDOP) by the additional secondary factor correction technology. This is the most economical solution for a land-based positioning system to complement the GNSS for the navigation safety of vessels sailing along coasts. PMID:26569258

  12. Recombinant cold-adapted trypsin I from Atlantic cod-expression, purification, and identification.

    PubMed

    Jónsdóttir, Gudrún; Bjarnason, Jón Bragi; Gudmundsdóttir, Agústa

    2004-01-01

    Atlantic cod trypsin I is a cold-adapted proteolytic enzyme exhibiting approximately 20 times higher catalytic efficiency (kcat/KM) than its mesophilic bovine counterpart for the simple amide substrate BAPNA. In general, cold-adapted proteolytic enzymes are sensitive to autolytic degradation, thermal inactivation as well as molecular aggregation, even at temperatures as low as 18-25 degrees C which may explain the problems observed with their expression, activation, and purification. Prior to the data presented here, there have been no reports in the literature on the expression of psychrophilic or cold-adapted proteolytic enzymes from fish. Nevertheless, numerous cold-adapted proteolytic microbial enzymes have been successfully expressed in bacteria and yeast. This report describes successful expression, activation, and purification of the recombinant cod trypsin I in the His-Patch ThioFusion Escherichia coli expression system. The E. coli pThioHis expression vector used in the study enabled the formation of a fusion protein between a highly soluble fraction of HP-thioredoxin contained in the vector and the N-terminal end of the precursor form of cod trypsin I. The HP-thioredoxin part of the fusion protein binds to a metal-chelating ProBond column, which facilitated its purification. The cod trypsin I part of the purified fusion protein was released by proteolytic cleavage, resulting in concomitant activation of the recombinant enzyme. The recombinant cod trypsin I was purified to homogeneity on a trypsin-specific benzamidine affinity column. The identity of the recombinant enzyme was demonstrated by electrophoresis and chromatography.

  13. Biologically-motivated system identification: application to microbial growth modeling.

    PubMed

    Yan, Jinyao; Deller, J R

    2014-01-01

    This paper presents a new method for identification of system models that are linear in parametric structure, but arbitrarily nonlinear in signal operations. The strategy blends traditional system identification methods with three modeling strategies that are not commonly employed in signal processing: linear-time-invariant-in-parameters models, set-based parameter identification, and evolutionary selection of the model structure. This paper reports recent advances in the theoretical foundation of the methods, then focuses on the operation and performance of the approach, particularly the evolutionary model determination. The method is applied to the modeling of microbial growth by Monod Kinetics.

  14. Research of Uncertainty Reasoning in Pineapple Disease Identification System

    NASA Astrophysics Data System (ADS)

    Liu, Liqun; Fan, Haifeng

    In order to deal with the uncertainty of evidences mostly existing in pineapple disease identification system, a reasoning model based on evidence credibility factor was established. The uncertainty reasoning method is discussed,including: uncertain representation of knowledge, uncertain representation of rules, uncertain representation of multi-evidences and update of reasoning rules. The reasoning can fully reflect the uncertainty in disease identification and reduce the influence of subjective factors on the accuracy of the system.

  15. Control of adaptive immunity by the innate immune system

    PubMed Central

    Iwasaki, Akiko; Medzhitov, Ruslan

    2015-01-01

    Microbial infections are recognized by the innate immune system both to elicit immediate defense and to generate long-lasting adaptive immunity. To detect and respond to vastly different groups of pathogens, the innate immune system uses several recognition systems that rely on sensing common structural and functional features associated with different classes of microorganisms. These recognition systems determine microbial location, viability, replication and pathogenicity. Detection of these features by recognition pathways of the innate immune system is translated into different classes of effector responses though specialized populations of dendritic cells. Multiple mechanisms for the induction of immune responses are variations on a common design principle wherein the cells that sense infections produce one set of cytokines to induce lymphocytes to produce another set of cytokines, which in turn activate effector responses. Here we discuss these emerging principles of innate control of adaptive immunity. PMID:25789684

  16. Classrooms as Complex Adaptive Systems: A Relational Model

    ERIC Educational Resources Information Center

    Burns, Anne; Knox, John S.

    2011-01-01

    In this article, we describe and model the language classroom as a complex adaptive system (see Logan & Schumann, 2005). We argue that linear, categorical descriptions of classroom processes and interactions do not sufficiently explain the complex nature of classrooms, and cannot account for how classroom change occurs (or does not occur), over…

  17. Aptitudes and Symbol Systems in Adaptive Classroom Teaching.

    ERIC Educational Resources Information Center

    Snow, Richard E.

    1997-01-01

    Education at its best is an "aptitude development program" that promotes development of learning abilities and effective personal styles needed for future learning in school and throughout life. Much of this development involves adapting and expanding the symbol systems used in teaching and learning to convey essential meanings. Adaptive…

  18. Adaptive mechanism-based congestion control for networked systems

    NASA Astrophysics Data System (ADS)

    Liu, Zhi; Zhang, Yun; Chen, C. L. Philip

    2013-03-01

    In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.

  19. Adaptive comanagement for building resilience in social-ecological systems.

    PubMed

    Olsson, Per; Folke, Carl; Berkes, Fikret

    2004-07-01

    Ecosystems are complex adaptive systems that require flexible governance with the ability to respond to environmental feedback. We present, through examples from Sweden and Canada, the development of adaptive comanagement systems, showing how local groups self-organize, learn, and actively adapt to and shape change with social networks that connect institutions and organizations across levels and scales and that facilitate information flows. The development took place through a sequence of responses to environmental events that widened the scope of local management from a particular issue or resource to a broad set of issues related to ecosystem processes across scales and from individual actors, to group of actors to multiple-actor processes. The results suggest that the institutional and organizational landscapes should be approached as carefully as the ecological in order to clarify features that contribute to the resilience of social-ecological systems. These include the following: vision, leadership, and trust; enabling legislation that creates social space for ecosystem management; funds for responding to environmental change and for remedial action; capacity for monitoring and responding to environmental feedback; information flow through social networks; the combination of various sources of information and knowledge; and sense-making and arenas of collaborative learning for ecosystem management. We propose that the self-organizing process of adaptive comanagement development, facilitated by rules and incentives of higher levels, has the potential to expand desirable stability domains of a region and make social-ecological systems more robust to change.

  20. Complex Adaptive Systems as Metaphors for Organizational Management

    ERIC Educational Resources Information Center

    Palmberg, Klara

    2009-01-01

    Purpose: The purpose of this paper is to explore the concept of complex adaptive systems (CAS) from the perspective of managing organizations, to describe and explore the management principles in a case study of an organization with unconventional ways of management and to present a tentative model for managing organizations as CAS--system…

  1. Enhancing Adaptive Filtering Approaches for Land Data Assimilation Systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Recent work has presented the initial application of adaptive filtering techniques to land surface data assimilation systems. Such techniques are motivated by our current lack of knowledge concerning the structure of large-scale error in either land surface modeling output or remotely-sensed estima...

  2. The New Trends in Adaptive Educational Hypermedia Systems

    ERIC Educational Resources Information Center

    Somyürek, Sibel

    2015-01-01

    This paper aims to give a general review of existing literature on adaptive educational hypermedia systems and to reveal technological trends and approaches within these studies. Fifty-six studies conducted between 2002 and 2012 were examined, to identify prominent themes and approaches. According to the content analysis, the new technological…

  3. Modeling Students' Memory for Application in Adaptive Educational Systems

    ERIC Educational Resources Information Center

    Pelánek, Radek

    2015-01-01

    Human memory has been thoroughly studied and modeled in psychology, but mainly in laboratory setting under simplified conditions. For application in practical adaptive educational systems we need simple and robust models which can cope with aspects like varied prior knowledge or multiple-choice questions. We discuss and evaluate several models of…

  4. The Transfer of Abstract Principles Governing Complex Adaptive Systems

    ERIC Educational Resources Information Center

    Goldstone, Robert L.; Sakamoto, Yasuaki

    2003-01-01

    Four experiments explored participants' understanding of the abstract principles governing computer simulations of complex adaptive systems. Experiments 1, 2, and 3 showed better transfer of abstract principles across simulations that were relatively dissimilar, and that this effect was due to participants who performed relatively poorly on the…

  5. Adaptive control system having hedge unit and related apparatus and methods

    NASA Technical Reports Server (NTRS)

    Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)

    2003-01-01

    The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.

  6. Adaptive control system having hedge unit and related apparatus and methods

    NASA Technical Reports Server (NTRS)

    Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)

    2007-01-01

    The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.

  7. Parameter identification for nonlinear aerodynamic systems

    NASA Technical Reports Server (NTRS)

    Pearson, Allan E.

    1992-01-01

    Continuing work on frequency analysis for transfer function identification is discussed. A new study was initiated into a 'weighted' least squares algorithm within the context of the Fourier modulating function approach. The first phase of applying these techniques to the F-18 flight data is nearing completion, and these results are summarized.

  8. Guiding Climate Change Adaptation Within Vulnerable Natural Resource Management Systems

    NASA Astrophysics Data System (ADS)

    Bardsley, Douglas K.; Sweeney, Susan M.

    2010-05-01

    Climate change has the potential to compromise the sustainability of natural resources in Mediterranean climatic systems, such that short-term reactive responses will increasingly be insufficient to ensure effective management. There is a simultaneous need for both the clear articulation of the vulnerabilities of specific management systems to climate risk, and the development of appropriate short- and long-term strategic planning responses that anticipate environmental change or allow for sustainable adaptive management in response to trends in resource condition. Governments are developing climate change adaptation policy frameworks, but without the recognition of the importance of responding strategically, regional stakeholders will struggle to manage future climate risk. In a partnership between the South Australian Government, the Adelaide and Mt Lofty Ranges Natural Resource Management Board and the regional community, a range of available research approaches to support regional climate change adaptation decision-making, were applied and critically examined, including: scenario modelling; applied and participatory Geographical Information Systems modelling; environmental risk analysis; and participatory action learning. As managers apply ideas for adaptation within their own biophysical and socio-cultural contexts, there would be both successes and failures, but a learning orientation to societal change will enable improvements over time. A base-line target for regional responses to climate change is the ownership of the issue by stakeholders, which leads to an acceptance that effective actions to adapt are now both possible and vitally important. Beyond such baseline knowledge, the research suggests that there is a range of tools from the social and physical sciences available to guide adaptation decision-making.

  9. Adaptive multibeam concepts for traffic management satellite systems.

    NASA Technical Reports Server (NTRS)

    Bisaga, J. J.; Blank, H. A.; Klein, S. A.

    1973-01-01

    The analysis of the performance of the various implementations of the simultaneous system in the Atlantic and Pacific Oceans has demonstrated that the use of adaptive system concepts in satellite traffic management systems can greatly improve the performance capabilities of these systems as compared to the corresponding performance capabilities of conventional nonadaptive satellite communications systems. It is considered that the techniques developed and analyzed represent a significant technological advance, and that the performance improvement achieved will generally outweigh the increased cost and implementation factors.

  10. Integrated modeling of the GMT laser tomography adaptive optics system

    NASA Astrophysics Data System (ADS)

    Piatrou, Piotr

    2014-08-01

    Laser Tomography Adaptive Optics (LTAO) is one of adaptive optics systems planned for the Giant Magellan Telescope (GMT). End-to-end simulation tools that are able to cope with the complexity and computational burden of the AO systems to be installed on the extremely large telescopes such as GMT prove to be an integral part of the GMT LTAO system development endeavors. SL95, the Fortran 95 Simulation Library, is one of the software tools successfully used for the LTAO system end-to-end simulations. The goal of SL95 project is to provide a complete set of generic, richly parameterized mathematical models for key elements of the segmented telescope wavefront control systems including both active and adaptive optics as well as the models for atmospheric turbulence, extended light sources like Laser Guide Stars (LGS), light propagation engines and closed-loop controllers. The library is implemented as a hierarchical collection of classes capable of mutual interaction, which allows one to assemble complex wavefront control system configurations with multiple interacting control channels. In this paper we demonstrate the SL95 capabilities by building an integrated end-to-end model of the GMT LTAO system with 7 control channels: LGS tomography with Adaptive Secondary and on-instrument deformable mirrors, tip-tilt and vibration control, LGS stabilization, LGS focus control, truth sensor-based dynamic noncommon path aberration rejection, pupil position control, SLODAR-like embedded turbulence profiler. The rich parameterization of the SL95 classes allows to build detailed error budgets propagating through the system multiple errors and perturbations such as turbulence-, telescope-, telescope misalignment-, segment phasing error-, non-common path-induced aberrations, sensor noises, deformable mirror-to-sensor mis-registration, vibration, temporal errors, etc. We will present a short description of the SL95 architecture, as well as the sample GMT LTAO system simulation

  11. Identification of the nonlinear vibration system of power transformers

    NASA Astrophysics Data System (ADS)

    Jing, Zheng; Hai, Huang; Pan, Jie; Yanni, Zhang

    2017-01-01

    This paper focuses on the identification of the nonlinear vibration system of power transformers. A Hammerstein model is used to identify the system with electrical inputs and the vibration of the transformer tank as the output. The nonlinear property of the system is modelled using a Fourier neural network consisting of a nonlinear element and a linear dynamic block. The order and weights of the network are determined based on the Lipschitz criterion and the back-propagation algorithm. This system identification method is tested on several power transformers. Promising results for predicting the transformer vibration and extracting system parameters are presented and discussed.

  12. Flexible Ubiquitous Learning Management System Adapted to Learning Context

    NASA Astrophysics Data System (ADS)

    Jeong, Ji-Seong; Kim, Mihye; Park, Chan; Yoo, Jae-Soo; Yoo, Kwan-Hee

    This paper proposes a u-learning management system (ULMS) appropriate to the ubiquitous learning environment, with emphasis on the significance of context awareness and adaptation in learning. The proposed system supports the basic functions of an e-learning management system and incorporates a number of tools and additional features to provide a more customized learning service. The proposed system automatically corresponds to various forms of user terminal without modifying the existing system. The functions, formats, and course learning activities of the system are dynamically and adaptively constructed at runtime according to user terminals, course types, pedagogical goals as well as student characteristics and learning context. A prototype for university use has been implemented to demonstrate and evaluate the proposed approach. We regard the proposed ULMS as an ideal u-learning system because it can not only lead students into continuous and mobile 'anytime, anywhere' learning using any kind of terminal, but can also foster enhanced self-directed learning through the establishment of an adaptive learning environment.

  13. Adaptive Optics System Design and Operation at Lick Observatory

    NASA Astrophysics Data System (ADS)

    Olivier, S. S.; Max, C. E.; Avicola, K.; Bissinger, H. D.; Brase, J. M.; Friedman, H. W.; Gavel, D. T.; Salmon, J. T.; Waltjen, K. E.

    1993-12-01

    An adaptive optics system developed for the 40 inch Nickel and 120 inch Shane telescopes at Lick Observatory is described. The adaptive optics system design is based on a 69 actuator continuous-surface deformable mirror and a Hartmann wavefront sensor equipped with a commercial intensified CCD fast-framing camera. The system has been tested at the Cassegrain focus of the 40 inch Nickel telescope where the subaperture diameter is 12 cm. The subaperture slope and mirror control calculations are performed on a four processor single board computer controlled by a Unix workstation. This configuration is capable of up to 1 KHz frame rates. The optical configuration of the system and its interface to the telescope is described. Details of the control system design, operation, and user interface are given. Initial test results emphasizing control system operations of this adaptive optics system using natural reference stars on the 40 inch Nickel telescope are presented. The initial test results are compared to predictions from analyses and simulations. Work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract W-7405-Eng-48.

  14. Adaptive backstepping slide mode control of pneumatic position servo system

    NASA Astrophysics Data System (ADS)

    Ren, Haipeng; Fan, Juntao

    2016-09-01

    With the price decreasing of the pneumatic proportional valve and the high performance micro controller, the simple structure and high tracking performance pneumatic servo system demonstrates more application potential in many fields. However, most existing control methods with high tracking performance need to know the model information and to use pressure sensor. This limits the application of the pneumatic servo system. An adaptive backstepping slide mode control method is proposed for pneumatic position servo system. The proposed method designs adaptive slide mode controller using backstepping design technique. The controller parameter adaptive law is derived from Lyapunov analysis to guarantee the stability of the system. A theorem is testified to show that the state of closed-loop system is uniformly bounded, and the closed-loop system is stable. The advantages of the proposed method include that system dynamic model parameters are not required for the controller design, uncertain parameters bounds are not need, and the bulk and expensive pressure sensor is not needed as well. Experimental results show that the designed controller can achieve better tracking performance, as compared with some existing methods.

  15. Generating Shifting Workloads to Benchmark Adaptability in Relational Database Systems

    NASA Astrophysics Data System (ADS)

    Rabl, Tilmann; Lang, Andreas; Hackl, Thomas; Sick, Bernhard; Kosch, Harald

    A large body of research concerns the adaptability of database systems. Many commercial systems already contain autonomic processes that adapt configurations as well as data structures and data organization. Yet there is virtually no possibility for a just measurement of the quality of such optimizations. While standard benchmarks have been developed that simulate real-world database applications very precisely, none of them considers variations in workloads produced by human factors. Today’s benchmarks test the performance of database systems by measuring peak performance on homogeneous request streams. Nevertheless, in systems with user interaction access patterns are constantly shifting. We present a benchmark that simulates a web information system with interaction of large user groups. It is based on the analysis of a real online eLearning management system with 15,000 users. The benchmark considers the temporal dependency of user interaction. Main focus is to measure the adaptability of a database management system according to shifting workloads. We will give details on our design approach that uses sophisticated pattern analysis and data mining techniques.

  16. A fast iterative recursive least squares algorithm for Wiener model identification of highly nonlinear systems.

    PubMed

    Kazemi, Mahdi; Arefi, Mohammad Mehdi

    2017-03-01

    In this paper, an online identification algorithm is presented for nonlinear systems in the presence of output colored noise. The proposed method is based on extended recursive least squares (ERLS) algorithm, where the identified system is in polynomial Wiener form. To this end, an unknown intermediate signal is estimated by using an inner iterative algorithm. The iterative recursive algorithm adaptively modifies the vector of parameters of the presented Wiener model when the system parameters vary. In addition, to increase the robustness of the proposed method against variations, a robust RLS algorithm is applied to the model. Simulation results are provided to show the effectiveness of the proposed approach. Results confirm that the proposed method has fast convergence rate with robust characteristics, which increases the efficiency of the proposed model and identification approach. For instance, the FIT criterion will be achieved 92% in CSTR process where about 400 data is used.

  17. Adaptive conventional power system stabilizer based on artificial neural network

    SciTech Connect

    Kothari, M.L.; Segal, R.; Ghodki, B.K.

    1995-12-31

    This paper deals with an artificial neural network (ANN) based adaptive conventional power system stabilizer (PSS). The ANN comprises an input layer, a hidden layer and an output layer. The input vector to the ANN comprises real power (P) and reactive power (Q), while the output vector comprises optimum PSS parameters. A systematic approach for generating training set covering wide range of operating conditions, is presented. The ANN has been trained using back-propagation training algorithm. Investigations reveal that the dynamic performance of ANN based adaptive conventional PSS is quite insensitive to wide variations in loading conditions.

  18. Design optimization of system level adaptive optical performance

    NASA Astrophysics Data System (ADS)

    Michels, Gregory J.; Genberg, Victor L.; Doyle, Keith B.; Bisson, Gary R.

    2005-09-01

    By linking predictive methods from multiple engineering disciplines, engineers are able to compute more meaningful predictions of a product's performance. By coupling mechanical and optical predictive techniques mechanical design can be performed to optimize optical performance. This paper demonstrates how mechanical design optimization using system level optical performance can be used in the development of the design of a high precision adaptive optical telescope. While mechanical design parameters are treated as the design variables, the objective function is taken to be the adaptively corrected optical imaging performance of an orbiting two-mirror telescope.

  19. Linear adaptive control of a single-tether system

    NASA Technical Reports Server (NTRS)

    Greene, M. E.; Carter, J. T.; Walls, J. L.

    1992-01-01

    A control law for a single-tether orbiting satellite system based on a reduced order linear adaptive control technique is presented. The main advantages of this technique are its design simplicity and the facts that specific system parameters and model linearization are not required when designing the controller. Two controllers are developed: one which uses only tension in the tether as control actuation and one which uses both tension and in-plane thrusters as control actuation. Both a sixth-order nonlinear and an 11th-order bead model of a tethered satellite system are used for simulation purposes, demonstrating the ability of the controller to manage an uncertain system. Retrieval and stationkeeping results using these nonlinear models and the linear adaptive controller demonstrate the feasibility of the method. The robustness of the controller with respect to parameter uncertainties is also demonstrated by changing the nonlinear model and parameters within the model without redesigning the controller.

  20. Variable Neural Adaptive Robust Control: A Switched System Approach

    SciTech Connect

    Lian, Jianming; Hu, Jianghai; Zak, Stanislaw H.

    2015-05-01

    Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewise quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.

  1. An Approach to Automated Fusion System Design and Adaptation

    PubMed Central

    Fritze, Alexander; Mönks, Uwe; Holst, Christoph-Alexander; Lohweg, Volker

    2017-01-01

    Industrial applications are in transition towards modular and flexible architectures that are capable of self-configuration and -optimisation. This is due to the demand of mass customisation and the increasing complexity of industrial systems. The conversion to modular systems is related to challenges in all disciplines. Consequently, diverse tasks such as information processing, extensive networking, or system monitoring using sensor and information fusion systems need to be reconsidered. The focus of this contribution is on distributed sensor and information fusion systems for system monitoring, which must reflect the increasing flexibility of fusion systems. This contribution thus proposes an approach, which relies on a network of self-descriptive intelligent sensor nodes, for the automatic design and update of sensor and information fusion systems. This article encompasses the fusion system configuration and adaptation as well as communication aspects. Manual interaction with the flexibly changing system is reduced to a minimum. PMID:28300762

  2. Guidance and Actuation Systems for an Adaptive-Suspension Vehicle

    DTIC Science & Technology

    1984-03-14

    FORM 1. REPORT NUMBER 2. GOVT ACCESSION NO. 3 . RECIPIENT’S CATALOG NUMBER G8186-685-84 ’D Ji 4. TITLE (and Subtitle) S. TYPE OF REPORT & PERIOD COVERED...Adaptive-Suspension Vehicle ..... ........ 2 2.2.2 The Terrain-Sensing System ...... .......... 3 2.3 Guidance System Algorithms... 3 2.3.1 Overview ............. ................... 3 2.3.2 Elevation Map Algorithms ...... ........... 3 2.3.3 Vehicle Guidance Algorithms

  3. System integration of pattern recognition, adaptive aided, upper limb prostheses

    NASA Technical Reports Server (NTRS)

    Lyman, J.; Freedy, A.; Solomonow, M.

    1975-01-01

    The requirements for successful integration of a computer aided control system for multi degree of freedom artificial arms are discussed. Specifications are established for a system which shares control between a human amputee and an automatic control subsystem. The approach integrates the following subsystems: (1) myoelectric pattern recognition, (2) adaptive computer aiding; (3) local reflex control; (4) prosthetic sensory feedback; and (5) externally energized arm with the functions of prehension, wrist rotation, elbow extension and flexion and humeral rotation.

  4. An information adaptive system study report and development plan

    NASA Technical Reports Server (NTRS)

    Ataras, W. S.; Eng, K.; Morone, J. J.; Beaudet, P. R.; Chin, R.

    1980-01-01

    The purpose of the information adaptive system (IAS) study was to determine how some selected Earth resource applications may be processed onboard a spacecraft and to provide a detailed preliminary IAS design for these applications. Detailed investigations of a number of applications were conducted with regard to IAS and three were selected for further analysis. Areas of future research and development include algorithmic specifications, system design specifications, and IAS recommended time lines.

  5. Modeling of Complex Adaptive Systems in Air Operations

    DTIC Science & Technology

    2006-09-01

    control of C3 in an increasingly complex military environment. Control theory is a multidisciplinary science associated with dynamic systems and, while...AFRL-IF-RS-TR-2006-282 In- House Final Technical Report September 2006 MODELING OF COMPLEX ADAPTIVE SYSTEMS IN AIR OPERATIONS...NOTICE AND SIGNATURE PAGE Using Government drawings, specifications, or other data included in this document for any purpose other than Government

  6. On Development of an Adaptive Tutoring System for Calculus Learning

    NASA Astrophysics Data System (ADS)

    Yokota, Hisashi

    2010-06-01

    One-on-one tutoring is known to be an effective model for learning calculus. Therefore, implementing one-on-one tutoring system into calculus learning software is a natural thing to do. The purpose of this article is to describe how to diagnose a students' knowledge structure about calculus without asking many questions and to show how an adaptive tutoring system is implemented into our calculus learning software JCALC.

  7. A Portable System for Nuclear, Chemical Agent and Explosives Identification

    SciTech Connect

    Parker, W.E.; Buckley, W.M.; Kreek, S.A.; Caffrey, A.J.; Mauger, G.J.; Lavietes, A.D.; Dougan, A.D.

    2000-09-29

    The FRIS/PINS hybrid integrates the LLNL-developed Field Radionuclide Identification System (FRIS) with the INEEL-developed Portable Isotopic Neutron Spectroscopy (PINS) chemical assay system to yield a combined general radioisotope, special nuclear material, and chemical weapons/explosives detection and identification system. The PINS system uses a neutron source and a high-purity germanium {gamma}-ray detector. The FRIS system uses an electrochemically cooled germanium detector and its own analysis software to detect and identify special nuclear material and other radioisotopes. The FRIS/PINS combined system also uses the electromechanically-cooled germanium detector. There is no other currently available integrated technology that can combine an active neutron interrogation and analysis capability for CWE with a passive radioisotope measurement and identification capability for special nuclear material.

  8. System identification methods for aircraft flight control development and validation

    NASA Technical Reports Server (NTRS)

    Tischler, Mark B.

    1995-01-01

    System-identification methods compose a mathematical model, or series of models, from measurements of inputs and outputs of dynamic systems. The extracted models allow the characterization of the response of the overall aircraft or component subsystem behavior, such as actuators and on-board signal processing algorithms. This paper discusses the use of frequency-domain system-identification methods for the development and integration of aircraft flight-control systems. The extraction and analysis of models of varying complexity from nonparametric frequency-responses to transfer-functions and high-order state-space representations is illustrated using the Comprehensive Identification from FrEquency Responses (CIFER) system-identification facility. Results are presented for test data of numerous flight and simulation programs at the Ames Research Center including rotorcraft, fixed-wing aircraft, advanced short takeoff and vertical landing (ASTOVL), vertical/short takeoff and landing (V/STOL), tiltrotor aircraft, and rotor experiments in the wind tunnel. Excellent system characterization and dynamic response prediction is achieved for this wide class of systems. Examples illustrate the role of system-identification technology in providing an integrated flow of dynamic response data around the entire life-cycle of aircraft development from initial specifications, through simulation and bench testing, and into flight-test optimization.

  9. A portable air jet actuator device for mechanical system identification

    NASA Astrophysics Data System (ADS)

    Belden, Jesse; Staats, Wayne L.; Mazumdar, Anirban; Hunter, Ian W.

    2011-03-01

    System identification of limb mechanics can help diagnose ailments and can aid in the optimization of robotic limb control parameters and designs. An interesting fluid phenomenon—the Coandă effect—is utilized in a portable actuator to provide a stochastic binary force disturbance to a limb system. The design of the actuator is approached with the goal of creating a portable device which could be deployed on human or robotic limbs for in situ mechanical system identification. The viability of the device is demonstrated by identifying the parameters of an underdamped elastic beam system with fixed inertia and stiffness and variable damping. The nonparametric compliance impulse response yielded from the system identification is modeled as a second-order system and the resultant parameters are found to be in excellent agreement with those found using more traditional system identification techniques. The current design could be further miniaturized and developed as a portable, wireless, unrestrained mechanical system identification instrument for less intrusive and more widespread use.

  10. A portable air jet actuator device for mechanical system identification.

    PubMed

    Belden, Jesse; Staats, Wayne L; Mazumdar, Anirban; Hunter, Ian W

    2011-03-01

    System identification of limb mechanics can help diagnose ailments and can aid in the optimization of robotic limb control parameters and designs. An interesting fluid phenomenon--the Coandă effect--is utilized in a portable actuator to provide a stochastic binary force disturbance to a limb system. The design of the actuator is approached with the goal of creating a portable device which could be deployed on human or robotic limbs for in situ mechanical system identification. The viability of the device is demonstrated by identifying the parameters of an underdamped elastic beam system with fixed inertia and stiffness and variable damping. The nonparametric compliance impulse response yielded from the system identification is modeled as a second-order system and the resultant parameters are found to be in excellent agreement with those found using more traditional system identification techniques. The current design could be further miniaturized and developed as a portable, wireless, unrestrained mechanical system identification instrument for less intrusive and more widespread use.

  11. Selective adaptation to "oddball" sounds by the human auditory system.

    PubMed

    Simpson, Andrew J R; Harper, Nicol S; Reiss, Joshua D; McAlpine, David

    2014-01-29

    Adaptation to both common and rare sounds has been independently reported in neurophysiological studies using probabilistic stimulus paradigms in small mammals. However, the apparent sensitivity of the mammalian auditory system to the statistics of incoming sound has not yet been generalized to task-related human auditory perception. Here, we show that human listeners selectively adapt to novel sounds within scenes unfolding over minutes. Listeners' performance in an auditory discrimination task remains steady for the most common elements within the scene but, after the first minute, performance improves for distinct and rare (oddball) sound elements, at the expense of rare sounds that are relatively less distinct. Our data provide the first evidence of enhanced coding of oddball sounds in a human auditory discrimination task and suggest the existence of an adaptive mechanism that tracks the long-term statistics of sounds and deploys coding resources accordingly.

  12. Autonomous navigation system using a fuzzy adaptive nonlinear H∞ filter.

    PubMed

    Outamazirt, Fariz; Li, Fu; Yan, Lin; Nemra, Abdelkrim

    2014-09-19

    Although nonlinear H∞ (NH∞) filters offer good performance without requiring assumptions concerning the characteristics of process and/or measurement noises, they still require additional tuning parameters that remain fixed and that need to be determined through trial and error. To address issues associated with NH∞ filters, a new SINS/GPS sensor fusion scheme known as the Fuzzy Adaptive Nonlinear H∞ (FANH∞) filter is proposed for the Unmanned Aerial Vehicle (UAV) localization problem. Based on a real-time Fuzzy Inference System (FIS), the FANH∞ filter continually adjusts the higher order of the Taylor development thorough adaptive bounds  and adaptive disturbance attenuation , which significantly increases the UAV localization performance. The results obtained using the FANH∞ navigation filter are compared to the NH∞ navigation filter results and are validated using a 3D UAV flight scenario. The comparison proves the efficiency and robustness of the UAV localization process using the FANH∞ filter.

  13. Evolutionary adaptation of phenotypic plasticity in a synthetic microbial system

    NASA Astrophysics Data System (ADS)

    Tans, Sander

    2010-03-01

    While phenotypic plasticity -the capability to respond to the environment- is vital to organisms, tests of its adaptation have remained indecisive because constraints and selection in variable environments are unknown and entangled. We show that one can determine the phenotype-fitness landscape that specifies selection on plasticity, by uncoupling the environmental cue and stress in a genetically engineered microbial system. Evolutionary trajectories revealed genetic constraints in a regulatory protein, which imposed cross-environment trade-offs that favored specialization. However, depending on the synchronicity and amplitude of the applied cue and stress variations, adaptation could break constraints, resolve trade-offs, and evolve optimal phenotypes that exhibit qualitatively altered (inverse) responses to the cue. Our results provide a first step to explain the adaptive origins of complex behavior in heterogeneous environments.

  14. Astronomical coronagraphy with high-order adaptive optics systems

    NASA Astrophysics Data System (ADS)

    Lloyd, James P.; Graham, James R.; Kalas, Paul; Oppenheimer, Ben R.; Sivaramakrishnan, Anand; Makidon, Russell B.; Macintosh, Bruce A.; Max, Claire E.; Baudoz, Pierre; Kuhn, Jeff R.; Potter, Dan

    2001-12-01

    Space surveillance systems have recently been developed that exploit high order adaptive optics systems to take diffraction limited images in visible light on 4 meter class telescopes. Most astronomical targets are faint, thus driving astronomical AO systems towards larger subapertures, and thus longer observing wavelengths for diffraction limited imaging at moderate Strehl ratio. There is, however, a particular niche that can be exploited by turning these visible light space surveillance systems to astronomical use at infrared wavelengths. At the longer wavelengths, the Strehl ratio rises dramatically, thus placing more light into the diffracted Airy pattern compared to the atmospheric halo. A Lyot coronagraph can be used to suppress the diffracted light from an on axis star, and observe faint companions and debris disks around nearby, bright stars. These very high contrast objects can only be observed with much higher order adaptive optics systems than are presently available to the astronomical community. We describe simulations of high order adaptive optics coronagraphs, and outline a project to deploy an astronomical coronagraph at the Air Force AEOS facility at the Maui Space Surveillance System.

  15. People at the centre of complex adaptive health systems reform.

    PubMed

    Sturmberg, Joachim P; O'Halloran, Diana M; Martin, Carmel M

    2010-10-18

    Health systems are increasingly recognised to be complex adaptive systems (CASs), functionally characterised by their continuing and dynamic adaptation in response to core system drivers, or attractors. The core driver for our health system (and for the health reform strategies intended to achieve it) should clearly be the improvement of people's health - the personal experience of health, regardless of organic abnormalities; we contend that a patient-centred health system requires flexible localised decision making and resource use. The prevailing trend is to use disease protocols, financial management strategies and centralised control of siloed programs to manage our health system. This strategy is suggested to be fatally flawed, as: people's health and health experience as core system drivers are inevitably pre-empted by centralised and standardised strategies; the context specificity of personal experience and the capacity of local systems are overlooked; and in line with CAS patterns and characteristics, these strategies will lead to "unintended" consequences on all parts of the system. In Australia, there is still the time and opportunity for health system redesign that truly places people and their health at the core of the system.

  16. Homeostatic regulation of memory systems and adaptive decisions.

    PubMed

    Mizumori, Sheri J Y; Jo, Yong Sang

    2013-11-01

    While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The "multiple memory systems of the brain" have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result in

  17. Homeostatic Regulation of Memory Systems and Adaptive Decisions

    PubMed Central

    Mizumori, Sheri JY; Jo, Yong Sang

    2013-01-01

    While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The “multiple memory systems of the brain” have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result

  18. 78 FR 6732 - Changes to Standard Numbering System, Vessel Identification System, and Boating Accident Report...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-31

    ... SECURITY Coast Guard 33 CFR Parts 173, 174, 181, and 187 RIN 1625-AB45 Changes to Standard Numbering System, Vessel Identification System, and Boating Accident Report Database AGENCY: Coast Guard, DHS. ACTION: Rule... Numbering System, Vessel Identification System, and Boating Accident Report Database rule became...

  19. The smart cluster method - Adaptive earthquake cluster identification and analysis in strong seismic regions

    NASA Astrophysics Data System (ADS)

    Schaefer, Andreas M.; Daniell, James E.; Wenzel, Friedemann

    2017-03-01

    Earthquake clustering is an essential part of almost any statistical analysis of spatial and temporal properties of seismic activity. The nature of earthquake clusters and subsequent declustering of earthquake catalogues plays a crucial role in determining the magnitude-dependent earthquake return period and its respective spatial variation for probabilistic seismic hazard assessment. This study introduces the Smart Cluster Method (SCM), a new methodology to identify earthquake clusters, which uses an adaptive point process for spatio-temporal cluster identification. It utilises the magnitude-dependent spatio-temporal earthquake density to adjust the search properties, subsequently analyses the identified clusters to determine directional variation and adjusts its search space with respect to directional properties. In the case of rapid subsequent ruptures like the 1992 Landers sequence or the 2010-2011 Darfield-Christchurch sequence, a reclassification procedure is applied to disassemble subsequent ruptures using near-field searches, nearest neighbour classification and temporal splitting. The method is capable of identifying and classifying earthquake clusters in space and time. It has been tested and validated using earthquake data from California and New Zealand. A total of more than 1500 clusters have been found in both regions since 1980 with M m i n = 2.0. Utilising the knowledge of cluster classification, the method has been adjusted to provide an earthquake declustering algorithm, which has been compared to existing methods. Its performance is comparable to established methodologies. The analysis of earthquake clustering statistics lead to various new and updated correlation functions, e.g. for ratios between mainshock and strongest aftershock and general aftershock activity metrics.

  20. Adaptive feed array compensation system for reflector antenna surface distortion

    NASA Technical Reports Server (NTRS)

    Acosta, Roberto J.; Zaman, A.

    1989-01-01

    The feasibility of a closed loop adaptive feed array system for compensating reflector surface deformations has been investigated. The performance characteristics (gain, sidelobe level, pointing, etc.) of large communication antenna systems degrade as the reflector surface distorts mainly due to thermal effects from a varying solar flux. The compensating systems described in this report can be used to maintain the design performance characteristics independent of thermal effects on the reflector surface. The proposed compensating system employs the concept of conjugate field matching to adjust the feed array complex excitation coefficients.

  1. Contingency support using adaptive telemetry extractor and expert system technologies

    NASA Technical Reports Server (NTRS)

    Bryant, Thomas; Cruse, Bryant; Wende, Charles

    1987-01-01

    The 'telemetry analysis logic for operations support' prototype system constitutes an expert system that is charged with contingency planning for the NASA Hubble Space Telescope (HST); this system has demonstrated the feasibility of using an adaptive telemetry extractor/reformatter that is integrated with an expert system. A test case generated by a simulator has demonstrated the reduction of the time required for analysis of a complex series of failures to a few minutes, from the hour usually required. The HST's telemetry extractor will be able to read real-time engineering telemetry streams and disk-based data. Telemetry format changes will be handled almost instantaneously.

  2. A Comparison of a Brain-Based Adaptive System and a Manual Adaptable System for Invoking Automation

    NASA Technical Reports Server (NTRS)

    Bailey, Nathan R.; Scerbo, Mark W.; Freeman, Frederick G.; Mikulka, Peter J.; Scott, Lorissa A.

    2004-01-01

    Two experiments are presented that examine alternative methods for invoking automation. In each experiment, participants were asked to perform simultaneously a monitoring task and a resource management task as well as a tracking task that changed between automatic and manual modes. The monitoring task required participants to detect failures of an automated system to correct aberrant conditions under either high or low system reliability. Performance on each task was assessed as well as situation awareness and subjective workload. In the first experiment, half of the participants worked with a brain-based system that used their EEG signals to switch the tracking task between automatic and manual modes. The remaining participants were yoked to participants from the adaptive condition and received the same schedule of mode switches, but their EEG had no effect on the automation. Within each group, half of the participants were assigned to either the low or high reliability monitoring task. In addition, within each combination of automation invocation and system reliability, participants were separated into high and low complacency potential groups. The results revealed no significant effects of automation invocation on the performance measures; however, the high complacency individuals demonstrated better situation awareness when working with the adaptive automation system. The second experiment was the same as the first with one important exception. Automation was invoked manually. Thus, half of the participants pressed a button to invoke automation for 10 s. The remaining participants were yoked to participants from the adaptable condition and received the same schedule of mode switches, but they had no control over the automation. The results showed that participants who could invoke automation performed more poorly on the resource management task and reported higher levels of subjective workload. Further, those who invoked automation more frequently performed

  3. Fault Analysis of Space Station DC Power Systems-Using Neural Network Adaptive Wavelets to Detect Faults

    NASA Technical Reports Server (NTRS)

    Momoh, James A.; Wang, Yanchun; Dolce, James L.

    1997-01-01

    This paper describes the application of neural network adaptive wavelets for fault diagnosis of space station power system. The method combines wavelet transform with neural network by incorporating daughter wavelets into weights. Therefore, the wavelet transform and neural network training procedure become one stage, which avoids the complex computation of wavelet parameters and makes the procedure more straightforward. The simulation results show that the proposed method is very efficient for the identification of fault locations.

  4. A modular and hybrid connectionist system for speaker identification.

    PubMed

    Bennani, Y

    1995-07-01

    This paper presents and evaluates a modular/hybrid connectionist system for speaker identification. Modularity has emerged as a powerful technique for reducing the complexity of connectionist systems, and allowing a priori knowledge to be incorporated into their design. Text-independent speaker identification is an inherently complex task where the amount of training data is often limited. It thus provides an ideal domain to test the validity of the modular/hybrid connectionist approach. To achieve such identification, we develop, in this paper, an architecture based upon the cooperation of several connectionist modules, and a Hidden Markov Model module. When tested on a population of 102 speakers extracted from the DARPA-TIMIT database, perfect identification was obtained.

  5. Robust adaptive dynamic programming and feedback stabilization of nonlinear systems.

    PubMed

    Jiang, Yu; Jiang, Zhong-Ping

    2014-05-01

    This paper studies the robust optimal control design for a class of uncertain nonlinear systems from a perspective of robust adaptive dynamic programming (RADP). The objective is to fill up a gap in the past literature of adaptive dynamic programming (ADP) where dynamic uncertainties or unmodeled dynamics are not addressed. A key strategy is to integrate tools from modern nonlinear control theory, such as the robust redesign and the backstepping techniques as well as the nonlinear small-gain theorem, with the theory of ADP. The proposed RADP methodology can be viewed as an extension of ADP to uncertain nonlinear systems. Practical learning algorithms are developed in this paper, and have been applied to the controller design problems for a jet engine and a one-machine power system.

  6. Embedded intelligent adaptive PI controller for an electromechanical system.

    PubMed

    El-Nagar, Ahmad M

    2016-09-01

    In this study, an intelligent adaptive controller approach using the interval type-2 fuzzy neural network (IT2FNN) is presented. The proposed controller consists of a lower level proportional - integral (PI) controller, which is the main controller and an upper level IT2FNN which tuning on-line the parameters of a PI controller. The proposed adaptive PI controller based on IT2FNN (API-IT2FNN) is implemented practically using the Arduino DUE kit for controlling the speed of a nonlinear DC motor-generator system. The parameters of the IT2FNN are tuned on-line using back-propagation algorithm. The Lyapunov theorem is used to derive the stability and convergence of the IT2FNN. The obtained experimental results, which are compared with other controllers, demonstrate that the proposed API-IT2FNN is able to improve the system response over a wide range of system uncertainties.

  7. MAC, A System for Automatically IPR Identification, Collection and Distribution

    NASA Astrophysics Data System (ADS)

    Serrão, Carlos

    Controlling Intellectual Property Rights (IPR) in the Digital World is a very hard challenge. The facility to create multiple bit-by-bit identical copies from original IPR works creates the opportunities for digital piracy. One of the most affected industries by this fact is the Music Industry. The Music Industry has supported huge losses during the last few years due to this fact. Moreover, this fact is also affecting the way that music rights collecting and distributing societies are operating to assure a correct music IPR identification, collection and distribution. In this article a system for automating this IPR identification, collection and distribution is presented and described. This system makes usage of advanced automatic audio identification system based on audio fingerprinting technology. This paper will present the details of the system and present a use-case scenario where this system is being used.

  8. Coronagraphy with the AEOS High Order Adaptive Optics System

    NASA Astrophysics Data System (ADS)

    Lloyd, J. P.; Graham, J. R.; Kalas, P.; Oppenheimer, B. R.; Sivaramakrishnan, A.; Makidon, R. B.; Macintosh, B. A.; Max, C. E.; Baudoz, P.; Kuhn, J. R.; Potter, D.

    2001-05-01

    Adaptive Optics has recently become a widely used technique to acquire sensitive, diffraction limited images in the near infrared with large ground based telescopes. Most astronomical targets are faint; driving astronomical AO systems towards large subapertures; resulting in a compromise between guide star brightness, observing wavelength, resolution and Strehl ratio. Space surveilance systems have recently been developed that exploit high order adaptive optics systems to take diffraction limited images in visible light on 4 meter class telescopes on bright (V<8) targets. There is, however, a particular niche that can be exploited by turning these visible light space surveillance systems to astronomical use at infrared wavelengths. At the longer wavelengths, the strehl ratio rises dramatically, thus placing more light into the diffracted Airy pattern at the expense of the atmospheric halo. A coronagraph can be used to suppress the diffracted light, and observe faint companions and debris disks around nearby, bright stars. Observations of these very high contrast objects benefit greatly from much higher order adaptive optics systems than are presently available to the astronomical commnunity. The National Science Foundation and Air Force Office of Scientific Research is sponsoring a program to conduct astronomical observations at the AEOS facility. We are presently developing an astronomical coronagraph to be deployed at the Air Force AEOS facility. We describe the coronagraph, and discuss the advantages and limitations of ground based high order AO for high contrast imaging.

  9. Evaluation of the Biolog automated microbial identification system

    NASA Technical Reports Server (NTRS)

    Klingler, J. M.; Stowe, R. P.; Obenhuber, D. C.; Groves, T. O.; Mishra, S. K.; Pierson, D. L.

    1992-01-01

    Biolog's identification system was used to identify 39 American Type Culture Collection reference taxa and 45 gram-negative isolates from water samples. Of the reference strains, 98% were identified to genus level and 76% to species level within 4 to 24 h. Identification of some authentic strains of Enterobacter, Klebsiella, and Serratia was unreliable. A total of 93% of the water isolates were identified.

  10. Some new results on system identification with dynamic neural networks.

    PubMed

    Yu, W; Li, X

    2001-01-01

    Nonlinear system online identification via dynamic neural networks is studied in this paper. The main contribution of the paper is that the passivity approach is applied to access several new stable properties of neuro identification. The conditions for passivity, stability, asymptotic stability, and input-to-state stability are established in certain senses. We conclude that the gradient descent algorithm for weight adjustment is stable in an L(infinity) sense and robust to any bounded uncertainties.

  11. Identification, Characterization, and Evaluation Criteria for Systems Engineering Agile Enablers

    DTIC Science & Technology

    2015-01-16

    monitoring communications in social media groups and websites (such as LinkedIn or Facebook groups associated with the Scaled Agile Framework, Lean... Identification , Characterization, and Evaluation Criteria for Systems Engineering Agile Enablers Technical Report SERC-2015-TR-049-1...currently valid OMB control number 1. REPORT DATE 16 JAN 2015 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE Identification

  12. Soft systems thinking and social learning for adaptive management.

    PubMed

    Cundill, G; Cumming, G S; Biggs, D; Fabricius, C

    2012-02-01

    The success of adaptive management in conservation has been questioned and the objective-based management paradigm on which it is based has been heavily criticized. Soft systems thinking and social-learning theory expose errors in the assumption that complex systems can be dispassionately managed by objective observers and highlight the fact that conservation is a social process in which objectives are contested and learning is context dependent. We used these insights to rethink adaptive management in a way that focuses on the social processes involved in management and decision making. Our approach to adaptive management is based on the following assumptions: action toward a common goal is an emergent property of complex social relationships; the introduction of new knowledge, alternative values, and new ways of understanding the world can become a stimulating force for learning, creativity, and change; learning is contextual and is fundamentally about practice; and defining the goal to be addressed is continuous and in principle never ends. We believe five key activities are crucial to defining the goal that is to be addressed in an adaptive-management context and to determining the objectives that are desirable and feasible to the participants: situate the problem in its social and ecological context; raise awareness about alternative views of a problem and encourage enquiry and deconstruction of frames of reference; undertake collaborative actions; and reflect on learning.

  13. Assistance using adaptive oscillators: robustness to errors in the identification of the limb parameters.

    PubMed

    Rinderknecht, Mike Domenik; Delaloye, Fabien André; Crespi, Alessandro; Ronsse, Renaud; Ijspeert, Auke Jan

    2011-01-01

    This paper provides a robustness analysis of the method we recently developed for rhythmic movement assistance using adaptive oscillators. An adaptive oscillator is a mathematical tool capable of extracting high-level features (i.e. amplitude, frequency, offset) of a quasi-sinusoidal measured movement, a rhythmic flexion-extension of the elbow in this case. By the use of a simple inverse dynamical model, the system can predict the torque produced by a human participant, such that a fraction of this estimated torque is fed back through a series elastic actuator to provide movement assistance. This paper objectives are twofold. First, we introduce a new 1 DOF assistive device developed in our lab. Second, we derive model-based predictions and conduct experimental validations to measure the variations in movement frequency as a function of the open parameters of the inverse dynamical model. As such, the paper provides an estimation of the robustness of our method due to model approximations. As main result, the paper reveals that the movement frequency is particularly robust to errors in the estimation of the damping coefficient. This is of high interest for the applicability of our approach, this parameter being in general the most difficult to identify.

  14. Application of an adaptive blade control algorithm to a gust alleviation system

    NASA Technical Reports Server (NTRS)

    Saito, S.

    1984-01-01

    The feasibility of an adaptive control system designed to alleviate helicopter gust induced vibration was analytically investigated for an articulated rotor system. This control system is based on discrete optimal control theory, and is composed of a set of measurements (oscillatory hub forces and moments), an identification system using a Kalman filter, a control system based on the minimization of the quadratic performance function, and a simulation system of the helicopter rotor. The gust models are step and sinusoidal vertical gusts. Control inputs are selected at the gust frequency, subharmonic frequency, and superharmonic frequency, and are superimposed on the basic collective and cyclic control inputs. The response to be reduced is selected to be that at the gust frequency because this is the dominant response compared with sub- and superharmonics. Numerical calculations show that the adaptive blade pitch control algorithm satisfactorily alleviates the hub gust response. Almost 100 percent reduction of the perturbation thrust response to a step gust and more than 50 percent reduction to a sinusoidal gust are achieved in the numerical simulations.

  15. Application of an adaptive blade control algorithm to a gust alleviation system

    NASA Technical Reports Server (NTRS)

    Saito, S.

    1983-01-01

    The feasibility of an adaptive control system designed to alleviate helicopter gust induced vibration was analytically investigated for an articulated rotor system. This control system is based on discrete optimal control theory, and is composed of a set of measurements (oscillatory hub forces and moments), an identification system using a Kalman filter, a control system based on the minimization of the quadratic performance function, and a simulation system of the helicopter rotor. The gust models are step and sinusoidal vertical gusts. Control inputs are selected at the gust frequency, subharmonic frequency, and superharmonic frequency, and are superimposed on the basic collective and cyclic control inputs. The response to be reduced is selected to be that at the gust frequency because this is the dominant response compared with sub- and superharmonics. Numerical calculations show that the adaptive blade pitch control algorithm satisfactorily alleviates the hub gust response. Almost 100% reduction of the perturbation thrust response to a step gust and more than 50% reduction to a sinusoidal gust are achieved in the numerical simulations.

  16. Algebraic and adaptive learning in neural control systems

    NASA Astrophysics Data System (ADS)

    Ferrari, Silvia

    A systematic approach is developed for designing adaptive and reconfigurable nonlinear control systems that are applicable to plants modeled by ordinary differential equations. The nonlinear controller comprising a network of neural networks is taught using a two-phase learning procedure realized through novel techniques for initialization, on-line training, and adaptive critic design. A critical observation is that the gradients of the functions defined by the neural networks must equal corresponding linear gain matrices at chosen operating points. On-line training is based on a dual heuristic adaptive critic architecture that improves control for large, coupled motions by accounting for actual plant dynamics and nonlinear effects. An action network computes the optimal control law; a critic network predicts the derivative of the cost-to-go with respect to the state. Both networks are algebraically initialized based on prior knowledge of satisfactory pointwise linear controllers and continue to adapt on line during full-scale simulations of the plant. On-line training takes place sequentially over discrete periods of time and involves several numerical procedures. A backpropagating algorithm called Resilient Backpropagation is modified and successfully implemented to meet these objectives, without excessive computational expense. This adaptive controller is as conservative as the linear designs and as effective as a global nonlinear controller. The method is successfully implemented for the full-envelope control of a six-degree-of-freedom aircraft simulation. The results show that the on-line adaptation brings about improved performance with respect to the initialization phase during aircraft maneuvers that involve large-angle and coupled dynamics, and parameter variations.

  17. Digital adaptive optics line-scanning confocal imaging system.

    PubMed

    Liu, Changgeng; Kim, Myung K

    2015-01-01

    A digital adaptive optics line-scanning confocal imaging (DAOLCI) system is proposed by applying digital holographic adaptive optics to a digital form of line-scanning confocal imaging system. In DAOLCI, each line scan is recorded by a digital hologram, which allows access to the complex optical field from one slice of the sample through digital holography. This complex optical field contains both the information of one slice of the sample and the optical aberration of the system, thus allowing us to compensate for the effect of the optical aberration, which can be sensed by a complex guide star hologram. After numerical aberration compensation, the corrected optical fields of a sequence of line scans are stitched into the final corrected confocal image. In DAOLCI, a numerical slit is applied to realize the confocality at the sensor end. The width of this slit can be adjusted to control the image contrast and speckle noise for scattering samples. DAOLCI dispenses with the hardware pieces, such as Shack–Hartmann wavefront sensor and deformable mirror, and the closed-loop feedbacks adopted in the conventional adaptive optics confocal imaging system, thus reducing the optomechanical complexity and cost. Numerical simulations and proof-of-principle experiments are presented that demonstrate the feasibility of this idea.

  18. Adaptive control of artificial pancreas systems - a review.

    PubMed

    Turksoy, Kamuran; Cinar, Ali

    2014-01-01

    Artificial pancreas (AP) systems offer an important improvement in regulating blood glucose concentration for patients with type 1 diabetes, compared to current approaches. AP consists of sensors, control algorithms and an insulin pump. Different AP control algorithms such as proportional-integral-derivative, model-predictive control, adaptive control, and fuzzy logic control have been investigated in simulation and clinical studies in the past three decades. The variability over time and complexity of the dynamics of blood glucose concentration, unsteady disturbances such as meals, time-varying delays on measurements and insulin infusion, and noisy data from sensors create a challenging system to AP. Adaptive control is a powerful control technique that can deal with such challenges. In this paper, a review of adaptive control techniques for blood glucose regulation with an AP system is presented. The investigations and advances in technology produced impressive results, but there is still a need for a reliable AP system that is both commercially viable and appealing to patients with type 1 diabetes.

  19. Risk-return relationship in a complex adaptive system.

    PubMed

    Song, Kunyu; An, Kenan; Yang, Guang; Huang, Jiping

    2012-01-01

    For survival and development, autonomous agents in complex adaptive systems involving the human society must compete against or collaborate with others for sharing limited resources or wealth, by using different methods. One method is to invest, in order to obtain payoffs with risk. It is a common belief that investments with a positive risk-return relationship (namely, high risk high return and vice versa) are dominant over those with a negative risk-return relationship (i.e., high risk low return and vice versa) in the human society; the belief has a notable impact on daily investing activities of investors. Here we investigate the risk-return relationship in a model complex adaptive system, in order to study the effect of both market efficiency and closeness that exist in the human society and play an important role in helping to establish traditional finance/economics theories. We conduct a series of computer-aided human experiments, and also perform agent-based simulations and theoretical analysis to confirm the experimental observations and reveal the underlying mechanism. We report that investments with a negative risk-return relationship have dominance over those with a positive risk-return relationship instead in such a complex adaptive systems. We formulate the dynamical process for the system's evolution, which helps to discover the different role of identical and heterogeneous preferences. This work might be valuable not only to complexity science, but also to finance and economics, to management and social science, and to physics.

  20. Digital adaptive optics line-scanning confocal imaging system

    PubMed Central

    Liu, Changgeng; Kim, Myung K.

    2015-01-01

    Abstract. A digital adaptive optics line-scanning confocal imaging (DAOLCI) system is proposed by applying digital holographic adaptive optics to a digital form of line-scanning confocal imaging system. In DAOLCI, each line scan is recorded by a digital hologram, which allows access to the complex optical field from one slice of the sample through digital holography. This complex optical field contains both the information of one slice of the sample and the optical aberration of the system, thus allowing us to compensate for the effect of the optical aberration, which can be sensed by a complex guide star hologram. After numerical aberration compensation, the corrected optical fields of a sequence of line scans are stitched into the final corrected confocal image. In DAOLCI, a numerical slit is applied to realize the confocality at the sensor end. The width of this slit can be adjusted to control the image contrast and speckle noise for scattering samples. DAOLCI dispenses with the hardware pieces, such as Shack–Hartmann wavefront sensor and deformable mirror, and the closed-loop feedbacks adopted in the conventional adaptive optics confocal imaging system, thus reducing the optomechanical complexity and cost. Numerical simulations and proof-of-principle experiments are presented that demonstrate the feasibility of this idea. PMID:26140334

  1. A new neuro-FDS definition for indirect adaptive control of unknown nonlinear systems using a method of parameter hopping.

    PubMed

    Boutalis, Yiannis; Theodoridis, Dimitris C; Christodoulou, Manolis A

    2009-04-01

    The indirect adaptive regulation of unknown nonlinear dynamical systems is considered in this paper. The method is based on a new neuro-fuzzy dynamical system (neuro-FDS) definition, which uses the concept of adaptive fuzzy systems (AFSs) operating in conjunction with high-order neural network functions (FHONNFs). Since the plant is considered unknown, we first propose its approximation by a special form of an FDS and then the fuzzy rules are approximated by appropriate HONNFs. Thus, the identification scheme leads up to a recurrent high-order neural network (RHONN), which however takes into account the fuzzy output partitions of the initial FDS. The proposed scheme does not require a priori experts' information on the number and type of input variable membership functions making it less vulnerable to initial design assumptions. Once the system is identified around an operation point, it is regulated to zero adaptively. Weight updating laws for the involved HONNFs are provided, which guarantee that both the identification error and the system states reach zero exponentially fast, while keeping all signals in the closed loop bounded. The existence of the control signal is always assured by introducing a novel method of parameter hopping, which is incorporated in the weight updating law. Simulations illustrate the potency of the method and comparisons with conventional approaches on benchmarking systems are given. Also, the applicability of the method is tested on a direct current (dc) motor system where it is shown that by following the proposed procedure one can obtain asymptotic regulation.

  2. Performance predictions for the Keck telescope adaptive optics system

    SciTech Connect

    Gavel, D.T.; Olivier, S.S.

    1995-08-07

    The second Keck ten meter telescope (Keck-11) is slated to have an infrared-optimized adaptive optics system in the 1997--1998 time frame. This system will provide diffraction-limited images in the 1--3 micron region and the ability to use a diffraction-limited spectroscopy slit. The AO system is currently in the preliminary design phase and considerable analysis has been performed in order to predict its performance under various seeing conditions. In particular we have investigated the point-spread function, energy through a spectroscopy slit, crowded field contrast, object limiting magnitude, field of view, and sky coverage with natural and laser guide stars.

  3. Design of high temperature adaptability cassegrain collimation system

    NASA Astrophysics Data System (ADS)

    Chen, Zhibin; Song, Yan; Liu, Xianhong; Xiao, Wenjian

    2014-12-01

    Collimation system is an indispensable part of the photoelectric detection equipment. Aimed at meeting the demand of field on-line detection for photoelectric system, the system must have higher requirements for its volume, quality and the anti-interference ability of all sorts of complex weather conditions. In order to solve this problem, this paper designed a kind of high temperature adaptability reflex cassegrain collimation system. First the technical indexes of the system was put forward according to the requirements of practical application, then the initial structure parameters was calculated by gaussian optical computing and optimized processing through Zemax. The simulation results showed that the MTF of the system was close to the diffraction limit, which had a good image quality. The system structure tube adopted hard steel material; the primary mirror and secondary mirror used low expansion coefficient of microcrystalline glass, which effectively reduced the deformation due to temperature difference and remained little change in quality and volume at the same time. The experiment results in high and low temperature environments also showed that the collimation system could keep within 30 "beam divergence angle, which proved to have good temperature adaptability, so that it can be used in the field of complex bad conditions.

  4. Nonlinear system identification and control based on modular neural networks.

    PubMed

    Puscasu, Gheorghe; Codres, Bogdan

    2011-08-01

    A new approach for nonlinear system identification and control based on modular neural networks (MNN) is proposed in this paper. The computational complexity of neural identification can be greatly reduced if the whole system is decomposed into several subsystems. This is obtained using a partitioning algorithm. Each local nonlinear model is associated with a nonlinear controller. These are also implemented by neural networks. The switching between the neural controllers is done by a dynamical switcher, also implemented by neural networks, that tracks the different operating points. The proposed multiple modelling and control strategy has been successfully tested on simulated laboratory scale liquid-level system.

  5. Complex Generalized Synchronization and Parameter Identification of Nonidentical Nonlinear Complex Systems

    PubMed Central

    Wang, Shibing; Wang, Xingyuan; Han, Bo

    2016-01-01

    In this paper, generalized synchronization (GS) is extended from real space to complex space, resulting in a new synchronization scheme, complex generalized synchronization (CGS). Based on Lyapunov stability theory, an adaptive controller and parameter update laws are designed to realize CGS and parameter identification of two nonidentical chaotic (hyperchaotic) complex systems with respect to a given complex map vector. This scheme is applied to synchronize a memristor-based hyperchaotic complex Lü system and a memristor-based chaotic complex Lorenz system, a chaotic complex Chen system and a memristor-based chaotic complex Lorenz system, as well as a memristor-based hyperchaotic complex Lü system and a chaotic complex Lü system with fully unknown parameters. The corresponding numerical simulations illustrate the feasibility and effectiveness of the proposed scheme. PMID:27014879

  6. Quantifying Adaptive Evolution in the Drosophila Immune System

    PubMed Central

    Obbard, Darren J.; Welch, John J.; Kim, Kang-Wook; Jiggins, Francis M.

    2009-01-01

    It is estimated that a large proportion of amino acid substitutions in Drosophila have been fixed by natural selection, and as organisms are faced with an ever-changing array of pathogens and parasites to which they must adapt, we have investigated the role of parasite-mediated selection as a likely cause. To quantify the effect, and to identify which genes and pathways are most likely to be involved in the host–parasite arms race, we have re-sequenced population samples of 136 immunity and 287 position-matched non-immunity genes in two species of Drosophila. Using these data, and a new extension of the McDonald-Kreitman approach, we estimate that natural selection fixes advantageous amino acid changes in immunity genes at nearly double the rate of other genes. We find the rate of adaptive evolution in immunity genes is also more variable than other genes, with a small subset of immune genes evolving under intense selection. These genes, which are likely to represent hotspots of host–parasite coevolution, tend to share similar functions or belong to the same pathways, such as the antiviral RNAi pathway and the IMD signalling pathway. These patterns appear to be general features of immune system evolution in both species, as rates of adaptive evolution are correlated between the D. melanogaster and D. simulans lineages. In summary, our data provide quantitative estimates of the elevated rate of adaptive evolution in immune system genes relative to the rest of the genome, and they suggest that adaptation to parasites is an important force driving molecular evolution. PMID:19851448

  7. Low Temperature Shape Memory Alloys for Adaptive, Autonomous Systems Project

    NASA Technical Reports Server (NTRS)

    Falker, John; Zeitlin, Nancy; Williams, Martha; Benafan, Othmane; Fesmire, James

    2015-01-01

    The objective of this joint activity between Kennedy Space Center (KSC) and Glenn Research Center (GRC) is to develop and evaluate the applicability of 2-way SMAs in proof-of-concept, low-temperature adaptive autonomous systems. As part of this low technology readiness (TRL) activity, we will develop and train low-temperature novel, 2-way shape memory alloys (SMAs) with actuation temperatures ranging from 0 C to 150 C. These experimental alloys will also be preliminary tested to evaluate their performance parameters and transformation (actuation) temperatures in low- temperature or cryogenic adaptive proof-of-concept systems. The challenge will be in the development, design, and training of the alloys for 2-way actuation at those temperatures.

  8. CRISPR-Cas systems: Prokaryotes upgrade to adaptive immunity.

    PubMed

    Barrangou, Rodolphe; Marraffini, Luciano A

    2014-04-24

    Clustered regularly interspaced short palindromic repeats (CRISPR), and associated proteins (Cas) comprise the CRISPR-Cas system, which confers adaptive immunity against exogenic elements in many bacteria and most archaea. CRISPR-mediated immunization occurs through the uptake of DNA from invasive genetic elements such as plasmids and viruses, followed by its integration into CRISPR loci. These loci are subsequently transcribed and processed into small interfering RNAs that guide nucleases for specific cleavage of complementary sequences. Conceptually, CRISPR-Cas shares functional features with the mammalian adaptive immune system, while also exhibiting characteristics of Lamarckian evolution. Because immune markers spliced from exogenous agents are integrated iteratively in CRISPR loci, they constitute a genetic record of vaccination events and reflect environmental conditions and changes over time. Cas endonucleases, which can be reprogrammed by small guide RNAs have shown unprecedented potential and flexibility for genome editing and can be repurposed for numerous DNA targeting applications including transcriptional control.

  9. A System Approach to Adaptive Multi-Modal Sensor Designs

    DTIC Science & Technology

    2010-02-01

    Email: rhody@cis.rit.edu Program Managers: Dr. Douglas Cochran <douglas.cochran@afosr.af.mil> Dr. Kitt C. Reinhardt <kitt.reinhardt...DEPARTMENT OF COMPUTER SCIENCE CONVENT AVE & 138TH ST SCHOOL OF ENGINEERING NEW YORK, NY 10031 Approved for public release...FA9550-08-1-0199 A System Approach to Adaptive Multi-Modal Sensor Designs 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d

  10. RAINBOW: Architecture-Based Adaptation of Complex Systems

    DTIC Science & Technology

    2005-04-01

    architectural level. The second problem is to translate architectural repairs into actual system changes. To do this we write a simple table-driven...bandwidth, regardless of the adaptation. Similarly, it is possible to use general probe technology to ameliorate the task of writing probes for particular...it is possible to use existing technologies like ProbeMeister [21] to generate the actual probes, without writing any additional code. 2.3

  11. Design of adaptive control systems by means of self-adjusting transversal filters

    NASA Technical Reports Server (NTRS)

    Merhav, S. J.

    1986-01-01

    The design of closed-loop adaptive control systems based on nonparametric identification was addressed. Implementation is by self-adjusting Least Mean Square (LMS) transversal filters. The design concept is Model Reference Adaptive Control (MRAC). Major issues are to preserve the linearity of the error equations of each LMS filter, and to prevent estimation bias that is due to process or measurement noise, thus providing necessary conditions for the convergence and stability of the control system. The controlled element is assumed to be asymptotically stable and minimum phase. Because of the nonparametric Finite Impulse Response (FIR) estimates provided by the LMS filters, a-priori information on the plant model is needed only in broad terms. Following a survey of control system configurations and filter design considerations, system implementation is shown here in Single Input Single Output (SISO) format which is readily extendable to multivariable forms. In extensive computer simulation studies the controlled element is represented by a second-order system with widely varying damping, natural frequency, and relative degree.

  12. A role of the adaptive immune system in glucose homeostasis

    PubMed Central

    Bronsart, Laura L; Contag, Christopher H

    2016-01-01

    Objective The immune system, including the adaptive immune response, has recently been recognized as having a significant role in diet-induced insulin resistance. In this study, we aimed to determine if the adaptive immune system also functions in maintaining physiological glucose homeostasis in the absence of diet-induced disease. Research design and methods SCID mice and immunocompetent control animals were phenotypically assessed for variations in metabolic parameters and cytokine profiles. Additionally, the glucose tolerance of SCID and immunocompetent control animals was assessed following introduction of a high-fat diet. Results SCID mice on a normal chow diet were significantly insulin resistant relative to control animals despite having less fat mass. This was associated with a significant increase in the innate immunity-stimulating cytokines granulocyte colony-stimulating factor, monocyte chemoattractant protein 1 (MCP1), and MCP3. Additionally, the SCID mouse phenotype was exacerbated in response to a high-fat diet as evidenced by the further significant progression of glucose intolerance. Conclusions These results support the notion that the adaptive immune system plays a fundamental biological role in glucose homeostasis, and that the absence of functional B and T cells results in disruption in the concentrations of various cytokines associated with macrophage proliferation and recruitment. Additionally, the absence of functional B and T cells is not protective against diet-induced pathology. PMID:27026807

  13. The plasma membrane transport systems and adaptation to salinity.

    PubMed

    Mansour, Mohamed Magdy F

    2014-11-15

    Salt stress represents one of the environmental challenges that drastically affect plant growth and yield. Evidence suggests that glycophytes and halophytes have a salt tolerance mechanisms working at the cellular level, and the plasma membrane (PM) is believed to be one facet of the cellular mechanisms. The responses of the PM transport proteins to salinity in contrasting species/cultivars were discussed. The review provides a comprehensive overview of the recent advances describing the crucial roles that the PM transport systems have in plant adaptation to salt. Several lines of evidence were presented to demonstrate the correlation between the PM transport proteins and adaptation of plants to high salinity. How alterations in these transport systems of the PM allow plants to cope with the salt stress was also addressed. Although inconsistencies exist in some of the information related to the responses of the PM transport proteins to salinity in different species/cultivars, their key roles in adaptation of plants to high salinity is obvious and evident, and cannot be precluded. Despite the promising results, detailed investigations at the cellular/molecular level are needed in some issues of the PM transport systems in response to salinity to further evaluate their implication in salt tolerance.

  14. Stepwise adaptation of murine cytomegalovirus to cells of a foreign host for identification of host range determinants.

    PubMed

    Ostermann, Eleonore; Pawletko, Kerstin; Indenbirken, Daniela; Schumacher, Uwe; Brune, Wolfram

    2015-06-01

    Ever since their first isolation 60 years ago, cytomegaloviruses have been recognized as being highly species specific. They replicate only in cells of their own or a closely related host species, while cells of phylogenetically more distant hosts are usually not permissive for viral replication. For instance, human cytomegalovirus replicates in human and chimpanzee fibroblasts but not in rodent cells, and murine cytomegalovirus (MCMV) replicates in cells of mice and rats but not in primate cells. However, the viral and cellular factors determining the narrow host range of cytomegaloviruses have remained largely unknown. We show that MCMV can be adapted stepwise to replicate in cultured human retinal pigment epithelial (RPE-1) cells and human fibroblasts. The human RPE-1 cells used for the initial adaptation step showed a pronounced contact inhibition and produced very low level of interferon-β transcripts upon cytomegalovirus infection, suggesting that these cells provide a particularly favorable environment for adaptation. By whole genome sequencing of the 230 kbp viral genomes of several adapted mutants, a limited number of mutations were detected. Comparison of several human cell-adapted MCMV clones and introduction of specific mutations into the wild-type MCMV genome by site-directed mutagenesis allows for the identification of viral host range determinants and provides the basis for elucidating the molecular basis of the cytomegalovirus host species specificity.

  15. Decentralized System Identification Using Stochastic Subspace Identification for Wireless Sensor Networks

    PubMed Central

    Cho, Soojin; Park, Jong-Woong; Sim, Sung-Han

    2015-01-01

    Wireless sensor networks (WSNs) facilitate a new paradigm to structural identification and monitoring for civil infrastructure. Conventional structural monitoring systems based on wired sensors and centralized data acquisition systems are costly for installation as well as maintenance. WSNs have emerged as a technology that can overcome such difficulties, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing is common practice, WSNs require decentralized computing algorithms to reduce data transmission due to the limitation associated with wireless communication. In this paper, the stochastic subspace identification (SSI) technique is selected for system identification, and SSI-based decentralized system identification (SDSI) is proposed to be implemented in a WSN composed of Imote2 wireless sensors that measure acceleration. The SDSI is tightly scheduled in the hierarchical WSN, and its performance is experimentally verified in a laboratory test using a 5-story shear building model. PMID:25856325

  16. Identification of open quantum systems from observable time traces

    DOE PAGES

    Zhang, Jun; Sarovar, Mohan

    2015-05-27

    Estimating the parameters that dictate the dynamics of a quantum system is an important task for quantum information processing and quantum metrology, as well as fundamental physics. In our paper we develop a method for parameter estimation for Markovian open quantum systems using a temporal record of measurements on the system. Furthermore, the method is based on system realization theory and is a generalization of our previous work on identification of Hamiltonian parameters.

  17. Numerical studies of identification in nonlinear distributed parameter systems

    NASA Technical Reports Server (NTRS)

    Banks, H. T.; Lo, C. K.; Reich, Simeon; Rosen, I. G.

    1989-01-01

    An abstract approximation framework and convergence theory for the identification of first and second order nonlinear distributed parameter systems developed previously by the authors and reported on in detail elsewhere are summarized and discussed. The theory is based upon results for systems whose dynamics can be described by monotone operators in Hilbert space and an abstract approximation theorem for the resulting nonlinear evolution system. The application of the theory together with numerical evidence demonstrating the feasibility of the general approach are discussed in the context of the identification of a first order quasi-linear parabolic model for one dimensional heat conduction/mass transport and the identification of a nonlinear dissipation mechanism (i.e., damping) in a second order one dimensional wave equation. Computational and implementational considerations, in particular, with regard to supercomputing, are addressed.

  18. Adaptive and Rational Anticipations in Risk Management Systems and Economy

    NASA Astrophysics Data System (ADS)

    Dubois, Daniel M.; Holmberg, Stig C.

    2010-11-01

    The global financial crisis of year 2009 is explained as a result of uncoordinated risk management decisions in business firms and economic organisations. The underlying reason for this can be found in the current financial system. As the financial market has lost much of its direct coupling to the concrete economy it provides misleading information to economic decision makers at all levels. Hence, the financial system has moved from a state of moderate and slow cyclical fluctuations into a state of fast and chaotic ones. Those misleading decisions can further be described, but not explained, by help of adaptive and rational expectations from macroeconomic theory. In this context, AE, the Adaptive Expectations are related to weak passive Exo-anticipation, and RE, the Rational expectations can be related to a strong, active and design oriented anticipation. The shortcomings of conventional cures, which builds on a reactive paradigm, have already been demonstrated in economic literature and are here further underlined by help of Ashby's "Law of Requisite Variety", Weaver's distinction between systems of "Disorganized Complexity" and those of "Organized Complexity", and Klir's "Reconstructability Analysis". Anticipatory decision-making is hence here proposed as a replacement to current expectation based and passive risk management. An anticipatory model of the business cycle is presented for supporting that proposition. The model, which is an extension of the Kaldor-Kalecki model, includes both retardation and anticipation. While cybernetics with the feedback process in control system deals with an explicit goal or purpose given to a system, the anticipatory system discussed here deals with a behaviour for which the future state of the system is built by the system itself, without explicit goal. A system with weak anticipation is based on a predictive model of the system, while a system with strong anticipation builds its own future by itself. Numerical simulations on

  19. An adaptive neuro-control system of synchronous generator for power system stabilization

    SciTech Connect

    Kobayashi, Takenori; Yokoyama, Akihiko

    1996-09-01

    This paper proposes a nonlinear adaptive generator control system using neural networks, called an adaptive neuro-control system (ANCS). This system generates supplementary control signals to conventional controllers and works adaptively in response to changes in operating conditions and network configuration. Through digital time simulations for a one-machine infinite bus test power system, the control performance of the ANCS and advanced controllers such as a linear optimal regulator and a self-tuning regulator is evaluated from the viewpoint of stability enhancement. As a result, the proposed ANCS using neural networks with nonlinear characteristics improves system damping more effectively and more adaptively than the other two controllers designed for the linearized model of the power system.

  20. Quasi-ARX wavelet network for SVR based nonlinear system identification

    NASA Astrophysics Data System (ADS)

    Cheng, Yu; Wang, Lan; Hu, Jinglu

    In this paper, quasi-ARX wavelet network (Q-ARX-WN) is proposed for nonlinear system identification. There are mainly two contributions are clarified. Firstly, compared with conventional wavelet networks (WNs), it is equipped with a linear structure, where WN is incorporated to interpret parameters of the linear ARX structure, thus Q-ARX-WN prediction model could be constructed and it is easy-to-use in nonlinear control. Secondly, guidelines for network construction are well considered due to the introduction of WNs, and Q-ARX-WN could be represented in a linear-in-parameter way. Therefore, linear support vector regression (SVR) based identification scheme may be introduced for the robust performance. Moreover, in adaptive control procedure, only linear parameters are needed to be adjusted when sudden changes have happened on the nonlinear system, thus the controller can track reference signal quickly. The effectiveness and robustness of the proposed nonlinear system identification method are validated by applying it to identify a real data system and a mathematical example, and an example of nonlinear system control is given to show usefulness of the proposed model.